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OSA Publishing > Biomedical Optics Express > Volume 5 > Issue 9 > Page 2988
Computed optical interferometric tomography for high-speed volumetric cellular imaging
Yuan-Zhi Liu, Nathan D. Shemonski, Steven G. Adie, Adeel Ahmad, Andrew J. Bower, P. Scott Carney, and Stephen A. Boppart
Yuan-Zhi Liu,1,2 Nathan D. Shemonski,1,2 Steven G. Adie,3 Adeel Ahmad,1,2 Andrew J. Bower,1,2 P. Scott Carney,1,2 and Stephen A. Boppart1,2,4,*
1Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 North Mathews Avenue, Urbana, Illinois 61801, USA
2Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 1406 West Green Street, Urbana, Illinois 61801, USA
3Department of Biomedical Engineering, Cornell University, 101 Weill Hall, Ithaca, New York 14853, USA
4Departments of Bioengineering, University of Illinois at Urbana-Champaign, 1304 West Springfield Avenue, Urbana, Illinois 61801, USA
*Corresponding author: boppart@illinois.edu
Y Liu
N Shemonski
S Adie
A Ahmad
A Bower
P Carney
S Boppart
Vol. 5,
pp. 2988-3000
•https://doi.org/10.1364/BOE.5.002988
Yuan-Zhi Liu, Nathan D. Shemonski, Steven G. Adie, Adeel Ahmad, Andrew J. Bower, P. Scott Carney, and Stephen A. Boppart, "Computed optical interferometric tomography for high-speed volumetric cellular imaging," Biomed. Opt. Express 5, 2988-3000 (2014)
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Ultrahigh speed spectral-domain optical coherence microscopy (BOE)
Computational optical coherence tomography [Invited] (BOE)
High-resolution optical coherence microscopy for high-speed, in vivo cellular imaging (OL)
Computational imaging
Optical imaging
Three dimensional imaging
Aberration compensation (090.1000)
Inverse scattering (100.3200)
Computational imaging (110.1758)
Optical coherence tomography (170.4500)
Three-dimensional microscopy (170.6900)
Interference microscopy (180.3170)
Original Manuscript: June 18, 2014
Revised Manuscript: August 5, 2014
Manuscript Accepted: August 6, 2014
Biomedical Optics Express Topics in Biomedical Optics from OSA's BIOMED 2014 Conference (2014)
3. Experimental results
4. Discussion and conclusions
Suppl. Mat. (1)
Equations (5)
Three-dimensional high-resolution imaging methods are important for cellular-level research. Optical coherence microscopy (OCM) is a low-coherence-based interferometry technology for cellular imaging with both high axial and lateral resolution. Using a high-numerical-aperture objective, OCM normally has a shallow depth of field and requires scanning the focus through the entire region of interest to perform volumetric imaging. With a higher-numerical-aperture objective, the image quality of OCM is affected by and more sensitive to aberrations. Interferometric synthetic aperture microscopy (ISAM) and computational adaptive optics (CAO) are computed imaging techniques that overcome the depth-of-field limitation and the effect of optical aberrations in optical coherence tomography (OCT), respectively. In this work we combine OCM with ISAM and CAO to achieve high-speed volumetric cellular imaging. Experimental imaging results of ex vivo human breast tissue, ex vivo mouse brain tissue, in vitro fibroblast cells in 3D scaffolds, and in vivo human skin demonstrate the significant potential of this technique for high-speed volumetric cellular imaging.
High-speed and high-resolution volumetric imaging is important for many areas of biology and medicine. For example, real-time imaging with cellular/subcellular-level resolution would improve imaging for intraoperative application and early cancer screening. Confocal microscopy [1], multiphoton microscopy [2], and optical coherence tomography (OCT) [3,4] are powerful techniques to image thick specimens and visualize microstructure in scattering tissue. High-speed confocal and multiphoton microscopy generate depth-sectioned images by scanning a focus across tissue through a high-numerical-aperture objective lens to achieve superior axial and transverse resolution for cellular imaging. To acquire a three-dimensional (3D) image volume, however, these techniques require a depth scan after which the different en face images are concatenated to forma so-called z-stack. This method is time consuming, and consequently is susceptible to motion artifacts. On the other hand, OCT utilizes low-coherence interferometry to measure the backscattered light from the sample. Using the so-called coherence gate, the transverse and axial resolutions in OCT are decoupled, and good axial resolution and large depth-of-field in scattering tissues are achieved by using a lower numerical aperture objective lens. As a result, for spectral-domain OCT (SD-OCT), raster scanning the beam in a transverse 2D plane allows 3D, volumetric imaging of the sample. However, the transverse resolution of OCT determined by the numerical aperture (NA) of the objective is usually 10–20 µm, which is insufficient to resolve cellular and subcellular features. Optical coherence microscopy (OCM) can be considered a combination of OCT and confocal microscopy. In addition to cellular level resolution in both the transverse and axial directions [5–7], OCM can achieve better image contrast and greater imaging depth by enhancing the rejection of multiply scattered light over noninterferometric and wide-field methods [8]. A high- NA objective lens is used to focus the optical beam tightly into the tissue and only provides en face imaging due to its very short confocal parameter. Therefore, there is a well-recognized tradeoff between the lateral resolution and the depth-of-focus.
To obtain 3D volumetric imaging with high transverse resolution, several methods have been developed for OCM, such as mechanical depth scanning [9–11], voltage-addressable focus shifting [12], and multi-beam focusing [13]. Various focus-depth extension methods have also been proposed and have shown potential for fast high resolution volumetric imaging, including hardware solutions, software additions, or a combination of the two. Examples are Bessel beam illumination [14,15], phase apodization [16], holoscopy [17], depth-encoded synthetic aperture [18], numerical refocusing [19], deconvolution [20], subaperture correlation based digital adaptive optics [21], and interferometric synthetic aperture microscopy (ISAM) [22,23]. Specifically, ISAM is a computed optical imaging technique that can achieve a spatially invariant lateral resolution for all the depths in the acquired 3D data set simultaneously by solving the inverse scattering problem. It is compatible with most common OCT/OCM system setups [24–27] and promising for many biomedical applications. Recently ISAM has been demonstrated as a robust technique for real-time in vivo volumetric imaging [28].
As the NA of the objective is increased to obtain better transverse resolution, wavefront aberrations become more evident. The traditional methods for correcting a wide range of optical aberrations require complicated and expensive optical instrumentation. However, even if the imaging system is well-designed, the specimen itself can also introduce aberrations [29]. Two common techniques use objectives with correction collars [30] or integrate adaptive optics [31]. But these methods increase system complexity and in general do not correct depth-dependent aberrations throughout the volumetric data set. In addition, the aberration correction needs to be optimized at the time of imaging, which is a challenge in certain applications. Previously, we have proposed a computed technique, computational adaptive optics (CAO) [32, 33], to correct aberrations in OCT, which uses an existing OCT/OCM system to correct the aberrations of the 3D volume during post-processing. Recently, a sub-aperture correlation-based digital adaptive optics technique has been developed to correct the aberrations. This method can directly provide the local wavefront gradient and automatically correct the aberrations without knowing the system parameters [21,34]. When compared to traditional z-stacking, these computational techniques provide a high-speed volumetric recording rate.
Until recently, ISAM and CAO experiments have been implemented in relatively low NA imaging systems (less than NA = 0.1). The resolution in these systems is not sufficient for cellular/subcellular imaging. In this paper, we constructed a high-resolution spectral-domain OCM (SD-OCM) system and utilized the combination of ISAM and CAO for high-speed volumetric imaging with cellular resolution. Ex vivo human breast tissue, ex vivo mouse brain tissue, in vitro cell dynamics in a 3D scaffold, and in vivo human skin were imaged to demonstrate the ability of this technique.
2.1 ISAM and CAO processing
Let ∼S(x,y,k) be the measured SD-OCM signal after wavenumber linearization with (x,y) as the transverse spatial dimensions. The 2D transverse Fourier transform of ∼S(x,y,k)is given by the expression [19]:
(1)S˜˜˜(qx,qy,k)=H(qx,qy,k)η˜˜˜[qx,qy,−(2k)2−(qx2+qy2)],
where η˜˜˜is the 3D Fourier transform of the attenuated scattering potentialη(x,y,z)=ρ(z)η0(x,y,z)and η0(x,y,z)is the scattering potential of the specimen to be detected. When within one Rayleigh length of the optical focus,ρ(z)=1, while beyond one Rayleigh length, the signal decays as ρ(z)=1/z [24]. In Eq. (1), kis the wavenumber, (qx,qy)are the transverse spatial frequencies, andH(qx,qy,k) gives the space-invariant axial and transverse spatial frequency response of the (ideal) system. The factor of 2 in Eq. (1) comes from the double-pass (reflection imaging) geometry. To properly invert Eq. (1), regularization (e.g. Tikhonov regularization) must also be performed. However, since H(qx,qy,k) is a smooth (within the system passband) Fourier-domain weighting, it represents simple linear shift-invariant filtering that will not introduce major distortions to the image [24,27,28,32]. For fast calculation, we neglect the Fourier-domain reweighting and implement only the resampling:
(2)η˜˜˜+(qx,qy,qz)≈S˜˜˜(qx,qy,k)|k=12qz2+qx2+qy2
where qzis the axial spatial frequency. For ISAM processing, resampling (k→qz) is performed in the Fourier domain to achieve a spatially invariant transverse resolution. The inverse problem, the inverse Fourier transform is applied and the 3D scattering potential of the specimen can be retrieved:
(3)η(x,y,z)=F−1[η˜˜˜+(qx,qy,qz)]
where F−1 stands for the 3D inverse Fourier transform. We note that the resampling in Eq. (2) can be divided into two separate 2D resampling steps to reduce memory requirements for real-time processing on a GPU [28].
If there are aberrations in the optical system, it is equivalent to the fact that the pupil function, which is the scaled Fourier transform of the point spread function (PSF), has a non-uniform phase distribution. We introduce a phase functionHA(qx,qy,k)to capture the aberrated transfer function, Eq. (1) can thus be modified as [32]
(4)S˜˜˜A(qx,qy,k)=HA(qx,qy,k)H(qx,qy,k)η˜˜˜[qx,qy,−(2k)2−(qx2+qy2)]
In hardware adaptive optics, the phase profile of the objective lens pupil is physically modified [32]. In CAO, we numerically modify the phase of a computed pupil function by multiplying the aberration correction filter HAC(qx,qy,k)=HA*(qx,qy,k) (the asterix '*' represents phase conjugation) with S˜˜˜A to compensate the aberration, producing
(5)S˜˜˜AC(qx,qy,k)=HAC(qx,qy,k)S˜˜˜A(qx,qy,k)
HAC(qx,qy,k)can be expressed as a phase function of Zernike polynomials [32] or it can be obtained by the guide star method [33]. After that, an inverse Fourier transform is applied to obtain the aberration-corrected reconstruction.
In practice, an efficient way to correct the 3D aberration is to first apply ISAM processing to correct the 3D defocus and then apply CAO for the en face plane images to correct the residual higher order aberrations. Hence, by combining Eqs. (2), (3), and (5), spatially invariant transverse resolution and aberration-free 3D reconstructions of OCM data are achieved in post-processing. In the current CAO method, we take a 2D Fourier transform of the en face plane image (complex) to obtain the virtual pupil function and multiply the phase filter HACto correct the aberration, and then use the inverse Fourier transform to obtain the aberration-corrected reconstruction. For the CAO method using Zernike polynomials, the phase filterHACis expressed as a phase function of a summation of Zernike polynomials. We manually adjust the coefficients of the Zernike polynomials and use image metrics to assess the image quality. For the point-like structures, or tissue containing a point-like signal, this point-like signal can be chosen as a guide star. The aberration HA is sensed by the phase difference between the virtual pupil functions of the aberrated guide star signal and the corresponding target PSF. The phase filter HAC can be obtained as the phase conjugation of the aberrated transfer functionHA. A more detailed explanation and implementation could be found in Ref [32] and [33].
2.2 Experimental setup
The experimental system is shown in Fig. 1. Measurements were acquired with a fiber-based spectral-domain (SD) OCM system based on a Michelson interferometer with a 50/50 coupler. Centered at 860 nm, a superluminescent diode (SLD) with a bandwidth of approximately 80 nm was used as the light source, giving a calculated axial resolution of 4.1 µm (Full Width at half Maximum, FWHM) in air. The spectrometer (Bayspec, Inc.) with a 4096 pixel line-scan camera (spL4096-140km, Basler) was interfaced to the PC via a National Instruments IMAQ board (NI-PCIe 1427) and operated at an A-scan rate of 60 kHz. The sample arm was built as a cage system to reduce phase fluctuations. With this high-speed recording rate and rigid system design, phase stability was assured during the imaging process and no phase noise correction was required [22]. A closely-spaced pair of galvanometer scanning mirrors (Cambridge Technology) was utilized for two-dimensional transverse scanning, which provided a compact geometry. The center point between the mirrors was imaged to the pupil plane in the objective lens (LUCPLFLN40X, Olympus, NA = 0.6) through a scan lens (f = 75 mm, AC254-075-B, Thorlabs) and a tube lens (f = 180 mm, U-TLUIR, Olympus). The coherence gate curvature caused by the non-telecentric setup, where the pivot of the scanning mechanism was not perfectly imaged to the back focal plane of the objective, was corrected computationally [35]. The system was constructed as an inverted microscope and the sample was placed on a coverslip with its surface of interest facing downward, which made it straightforward to obtain a flat optical surface suitable for live-cell studies. The power applied on the sample was about 3 mW, and the sensitivity of the system was 87 dB.
Fig. 1 Schematic of the inverted spectral-domain optical coherence microscope (SD-OCM) system operating with ISAM and CAO.
The transverse resolution, measured by sub-resolution particles (copper zinc iron oxide particles in PDMS, mean diameter < 100 nm), was found to be 0.6 µm (FWHM of the intensity profile). Figure 2 shows an OCM image of a USAF resolution target, where the finest structure (element 3 bars in group 9) can be clearly observed (1.56 µm spacing). The dip-to-peak ratio is approximately 30%, which is sufficient to distinguish the adjacent bars [36]. The high transverse and axial resolution provides the capability for cellular and subcellular level imaging. For an ideal Gaussian beam, the theoretical Rayleigh length is 0.8 μm. The measured Rayleigh length was 3.8 µm, which is larger than the theoretical value due to the aberrations.
Fig. 2 System characterization. OCM image of a USAF resolution target where the smallest element 3 bars in group 9 can be observed.
3.1 Phantom imaging
A tissue mimicking phantom consisting of copper zinc iron oxide particles (< 100 nm) embedded in PDMS was used to quantitatively evaluate the reconstruction quality. Figure 3(a) shows the average PSF FWHM as a function of distance from the focus for OCM, ISAM, and the combination of ISAM and CAO. It can be seen that for this high-NA setup, the transverse resolution degrades (the FWHM of PSF increases) quickly at planes that are away from the focus (green line). ISAM tends to smooth the rapid change in the PSF FWHM and provides a much flatter trend around the focus (red line). We noticed that the presence of aberrations dramatically affects the reconstruction results of ISAM, especially for the far-from-focus region [37]. Using Zernike polynomials and a guide star technique, CAO corrects the aberrations. The blue line shows a PSF width of less than 1 µm for all depths after applying both CAO and ISAM.
Fig. 3 Tissue phantom imaging (a) Experimental measurement of PSF (FWHM) versus distance from the focus for OCT, ISAM, and the combination of ISAM and CAO. (b)-(d) Cross-sectional images of the reconstructions of OCM, ISAM, the combination of ISAM and CAO. (e)-(g) En face plane reconstructions of OCM, ISAM, the combination of ISAM and CAO, at 28 µm below the focus. Spherical aberration can be seen clearly in the (e) OCM and (f) ISAM results. The insets show the zoomed-in images of selected particles in (e)-(g). All the images have the same gamma correction. The color scales indicate the displayed range of relative signal amplitudes. The scale bar denotes 20 µm.
Figures 3(b)-3(d) are cross-sectional images and Figs. 3(e)-3(g) are en face imaging results showing the influence of aberrations and the correction ability of CAO. From Figs. 3(b)-3(d), the narrower width of the point scatterers can be clearly seen along the depths. Because we used a phantom with sparse particles and the energy was focused into a much smaller space after the correction, especially in the transverse direction, some blurry patterns in the OCM cross-sectional images disappear in the ISAM and ISAM + CAO results. More detailed improvement can be seen from the en face images in Figs. 3(e)-3(g). The en face planes are at 28 µm below the focus, extracted from the same 3D data set in Fig. 3(a). The same gamma correction (γ = 0.5) was applied to the intensity scale of the three images to compress dynamic range. In Fig. 3(e), the ring-shaped structures caused by spherical aberrations can be clearly observed. The rings in the PSF are not circularly symmetric, indicating that other aberrations such as coma or astigmatism are present as well. Although ISAM [Fig. 3(f)] observably reduces the width of the PSF, the ring structures are still present. In Fig. 3(g), the combination of ISAM and CAO shows a significant improvement in the PSF. The sub-resolution particles are imaged as point-like structures, as they would be in the focus of the beam. From the color scale of the color bar, we can see that the highest intensity of the image (red) has been increased to more than 2.5 times (3.0/1.2) that from the combination of ISAM and CAO [Fig. 3(g)], compared to the OCM image alone [Fig. 3(e)].
3.2 Ex vivo cellular imaging
Figure 4 shows a series of en face images taken at different depths from a 3D reconstructed data set of ex vivo human breast tissue. The 1st row (a-c) shows the OCM-processed results while the 2nd row (d-f) shows the ISAM-processed results. Figures 4(a), 4(d) are the en face images at the focal plane, which are about 80 µm (optical) below the surface of the sample. Subcellular structures are clearly resolved by both OCM and ISAM. The fat cell membrane boundaries are sharp and the nuclei are readily distinguished as bright and highly scattering (indicated by the arrows).
Fig. 4 OCM (1st row) and ISAM (2nd row) in ex vivo human breast tissue. En face planes of OCM at (a) the focal plane, a plane (b) 22 µm (5.8 Rayleigh lengths) and (c) 67 µm (17.6 Rayleigh lengths) above the focus plane. (d)-(f) ISAM reconstruction of the same en face planes of (a)-(c). The bright and highly scattering nuclei are indicated by the arrows. The scale bar in (a) denotes 50 µm, and applies to all images.
However, as we move away from the focal plane the OCM images appear blurry due to the short confocal parameter, as seen in Figs. 4(b), 4(c), which are en face planes taken at 22 µm (5.8 Rayleigh lengths) and 67 µm (17.6 Rayleigh lengths) above the focal plane. In comparison, ISAM significantly improves OCM images by keeping the membrane boundaries sharp over different depths, revealing a spatially invariant high transverse resolution. As a result, ISAM dramatically extends the depth-of-field of OCM while maintaining the high transverse resolution. Using ISAM, 3D volumetric cellular imaging can be performed without scanning the focus in depth.
Two image metrics were computed to quantitatively evaluate the image quality along the depth. These plots are shown in Fig. 5. The first plots the depth-dependent signal-to-noise ratio (SNR) improvement. We used 90% quantiles of the intensity histograms as the depth-dependent signal [28] and the minimum local standard deviation of the image as the noise, which indicated the fluctuation of the background. The subtraction between the SNR of the ISAM data and the SNR of the OCM data shows the SNR improvement. The other image metric utilized was anisotropy, which measured the variance of the entropy upon a set of directions. This metric was originally devised to identify in-focus, noise-free images from other degraded versions in incoherent imaging systems [38]. Higher values in this metric indicate sharper structures and better image quality. From Fig. 5 we can see that these two image metrics show good agreement, and ISAM processing gives better image quality than OCM along different depths. Better SNR improvement is observable at the planes further from the focus because of the defocus correction. As the fat cells may act as a ball lens array, stronger signal was observed at the top and bottom membrane surfaces, which generated two main peaks (depth = 0 and depth at the focal plane) in Fig. 5(b).
Fig. 5 Image metrics for quantitatively evaluating the image quality of ex vivo human breast tissue along the depth. (a) Depth-dependent SNR improvement, based on subtracting the SNR between ISAM and OCM. (b) Image anisotropy measurement.
As a high-NA objective was used in the experiment, images are more sensitive to aberration, which may be caused by elements or misalignments within the optical imaging system or by the sample itself [29]. CAO provides a new way to correct the aberrations after acquiring the data. To demonstrate the further image impovement of utilizing CAO, Fig. 6 shows en face planes (about 6 Rayleigh lengths above the focus) from tomograms of an ex vivo mouse brain tissue (coronal section). From the ISAM-processed results [Fig. 6(b)], it can be seen that not only the cell bodies of neurons (dark regions, indicated by the blue arrows), but also the myelinated axons (the bright lines, indicated by the green arrows) are clearer compared to the OCM results [Fig. 6(a)]. To correct these aberrations, we applied CAO with Zernike polynomials [39] Z3,5 (astigmatism), Z4 (defocus), Z7,8 (coma), Z12 (spherical aberration) to modify the virtual pupil function of the en face plane and used image metrics (anisotropy [38] and power of image intensity [40]) for adjustment feedback. After CAO processing, Fig. 6(c) shows sharper features of the axons. The insets in Figs. 6(b), 6(c) show average profiles of myelinated axons and their quantified diameters by FWHM. The measured results of the myelinated axons (1.00 µm and 1.23 µm), after aberration correction, more closely match the known anatomical size range (0.1-1.5 µm) [41]. This verifies that the combination of ISAM and CAO can further improve the resolution and image quality for volumetric cellular imaging.
Fig. 6 En face planes from highly scattering ex vivo mouse brain tissue at a depth ~6 Rayleigh lengths above the focus, showing (a) OCM, (b) Uncorrected ISAM, and (c) CAO aberration-corrected ISAM. The blue arrows indicate the cell bodies of neurons, and the green arrows indicate the myelinated axons. The insets show the profile and FWHM of the myelinated axons. The scale bar denotes 20 µm.
3.3 In vitro cell dynamics
Because ISAM can dramatically extend the depth-of-field of normal OCM with high transverse resolution, it can achieve 3D volumetric cellular imaging by high-speed 2D scanning, which is promising for research investigating fast cell dynamics. Cell activities in 3D topographic scaffold structures are of great interest in tissue engineering research. In this paper, we use ISAM and CAO to investigate the dynamics of mouse dermal fibroblast cells in 3D macroporous alginate hydrogel scaffolds.
The 3D volumes were acquired by 512 × 512 transverse scanning at an A-scan rate of 60 kHz. Figure 7 shows the reconstruction results of an en face plane at about 43.7 µm (~11.5 Rayleigh lengths) above the focus. The OCM image [Fig. 7(a)] is quite blurry and it is difficult to recognize the structure of the scaffold. Compared to the OCM result, ISAM dramatically improves the reconstruction and clearly reconstructs the scaffold structures [Fig. 7(b)]. However, astigmatism was noticed as stretched point-like structures. Two representative aberrated structures selected from Fig. 7(b) were examined at high magnification and shown in Figs. 7(d), 7(e). We applied CAO in post-processing to correct these aberrations, as was done for the ex vivo brain tissue. The final aberration correction results are shown in Figs. 7(c), 7(f), 7(g). It can be seen that after CAO processing, the tail of the point-like structure has disappeared and better imaging performance is achieved.
Fig. 7 En face plane reconstructions of the 3D scaffold at a depth of about 11.5 Rayleigh lengths above the focus from (a) OCM, (b) ISAM without aberration correction, and (c) CAO and ISAM. The images in (f) and (g) show the same zoomed-in structures as in (d) and (e), but show the results of correcting the aberrations. The scale bar denotes 30 µm.
Utilizing ISAM and CAO, the size of the 3D volume was about 160 µm × 160 µm × 70 µm, with a lateral resolution of 0.6 µm and an axial resolution of 4 µm. The total depth is related to the focus position [28]. Acquisition time of each 3D data set was within 4.4 s and the total time-lapse measurement duration was about 2 hours. Figure 8 shows the results from two time points: 0 min and 112 min. Figures 8(a), 8(d), 8(g), 8(j) and Figs. 8(b), 8(e), 8(h), 8(k) are at the depth of approximately 12 and 5 Rayleigh lengths above the focus, respectively. Compared with traditional OCM, we can see that the scaffold structures at different depths in the 3D volume are clearly resolved by the ISAM/CAO reconstruction. Thus the application of computed imaging to OCM makes it possible to image the interactions between the cells and the scaffold and observe cell migrations over longer distances without having to repeatedly scan the focal plane each time. In this sample, the fibroblast cells mainly moved around within the focal plane [Figs. 8(c), 8(f), 8(i), 8(l)]. Over the course of 2 hours, we can see cells migrating towards the upper right corner. The filopodia were clearly observed during the movement, and are indicated by the arrow in Figs. 8(f), 8(l). The cell migration over 2 hours can be seen in the supplemental Media 1.
Fig. 8 Time lapse results of mouse dermal fibroblasts in a 3D macroporous alginate hydrogel scaffold (Media 1). Images (a-f) and (g-l) are the results for t = 0 min (start) and 112 min, respectively. The columns (a, d, g, j) are at the depth of about 12 Rayleigh lengths above the focus, and (b, e, h, k) are at the depth of about 5 Rayleigh lengths above the focus. Images (c, f, i, l) are at the focal plane. The top row images (a, b, c, g, h, i) are the OCM results while the bottom row images (d, e, f, j, k, l) show the results from applying the combination of ISAM and CAO. The green arrows indicate the filopodia. The scale bar denotes 30 µm.
3.4 In vivo cellular imaging
To demonstrate the capability of ISAM and CAO for high-speed, in vivo volumetric cellular imaging, 3D data of normal human skin (from the palm) were acquired from a healthy volunteer. An imaging mount, consisting of a coverslip and a rigid holder with a hole in the center, was attached to the cage system and used to keep the skin stabilized during image acquisition, similar in principle to those used for confocal microscopy [1]. Glycerol was applied between the skin and the coverslip to serve as an index-matching agent. All imaging was performed in accordance with a protocol approved by the Institutional Review Board at the University of Illinois at Urbana-Champaign. The acquired 3D volume with 0.6 µm lateral resolution and 4.1 µm axial resolution was 160 µm × 160 µm × 150 µm for x, y, and z dimensions after ISAM and CAO post-processing. The recorded 3D data set consisted of 4,096 pixels per A-scan and 512 A-scans along each transverse dimension. As only 2D transverse scanning was needed our total acquisition time was within 4.4 s, which is significantly faster than previous volumetric OCM acquisition methods that require scanning along the depth to obtain 3D data [42].
Figure 9 shows different en face planes extracted from the volumetric data set of the skin. The five columns represent 5 depth reconstructions using OCM and the combination of ISAM and CAO. The focus was placed at an approximate depth of 152 µm beneath the surface, near the junction region between the epidermis and dermis, as shown in Figs. 9(d), 9(i). For the OCM results, only the microstructures located around the focus can be seen. For example, the structures in the en face planes at about 24 and 21 Rayleigh lengths above the focus are totally washed out due to the defocus [Figs. 9(a), 9(b)]. As a comparison, after ISAM and CAO processing, the structures within various layers of the skin, from the epidermis through the superficial dermis and into the dermis, are clearly resolved [Figs. 9(f)-9(j)]. At a depth about 62 µm under the skin surface and 24 Rayleigh lengths above the focal plane, the transition between the stratum corneum and the epidermis, the boundary shown by the arrow, can be seen in Fig. 9(f). In Fig. 9(g), the nuclei of the granular cells become visible as dark areas surrounded by bright cytoplasm. Deeper in the skin, dermal papillae are visualized and indicated by the arrow in Fig. 9(h). From Fig. 9(i), we can clearly see the dermal-epidermal junction and the basal cells (indicated by the arrow), which have sizes smaller than the granular cells. Deep into the dermis, heterogeneous structure, most likely representing collagen fiber bundles, can be seen in Fig. 9(j). Overall, ISAM and CAO provide an approach to rapidly image the different layers and structures of in vivo human skin with cellular level resolution. It is reported that 85% of skin cancer originates in the epithelial layer [43]. One of the critical steps in differentiating cancer cells is significant nuclear enlargement, where the nuclei in the basal cell layer has a mean size around 6 µm [44]. Therefore, high resolution imaging of the entire epidermis could provide valuable information for performing skin cancer diagnosis. In vivo imaging utilizing ISAM and CAO shows great potential for applications in skin cancer research.
Fig. 9 Cellular resolution images of different layers in in vivo human skin. The 1st row are OCM results without Z-stacks, and the 2nd row are the results from the combination of ISAM and CAO. (a, f) Depth about 62 µm beneath the surface and 24 Rayleigh lengths above the focus, where the junction between the stratum corneum and the epidermis is located. The boundary of this junction is indicated by the arrow in (f). (b, g) Epidermis layer. The nuclei of granular cells are visible in ISAM/CAO results (arrow) while they are not present in the OCM result. (c, h) Superficial dermis layer. An arrow shows the dermal papillae. (d, i) Junction between epidermis and dermis. The basal cells are visualized and indicated by an arrow. (e, j) Deep in the dermis, which is about 11 Rayleigh lengths below the focus. Probable collagen fiber bundles are indicated by the arrow in the ISAM/CAO reconstruction. The scale bar in (a) denotes 40 µm, and applies to all images.
With this high-speed inverted SD-OCM system, we have performed volumetric cellular/subcellular imaging of ex vivo human breast tissue, ex vivo mouse brain tissue, in vitro fibroblast cell dynamics, and in vivo human skin tissue. Dramatic improvement of image quality within the entire imaging volume has been achieved by utilizing the computational optical imaging approaches of ISAM and CAO.
It is noted that in CAO, Z4 of the Zernike polynomials can also be used to correct the defocus on a two-dimensional en face plane image. However, it should be pointed out that the phase distribution of Z4, 2qx2 + 2qy2 −1, can be recognized as the paraxial approximation of the transfer function in ISAM,−(2k)2−(qx2+qy2)in Eq. (1) and Eq. (4). When using a high-NA objective in the experiment (e.g. OCM), the paraxial approximation cannot always be satisfied. A recent publication, Ref [21], also discusses this problem. The fast FM model they used is similar to Z4 we used in CAO, and the IS method they used is similar to our ISAM technique. Furthermore, ISAM could refocus the out-of-focus points in three dimensions because it solves the 3D inverse scattering problem for aberration-free OCT/OCM, not only dealing with the transverse spatial frequency but also the axial spatial frequency. A more detailed explanation of the transverse and axial blurring resulting from a point scatterer when imaging with high-NA can be found in our previous paper, for example, Fig. 4 and Fig. 5 in Ref [24]. Hence, in practice, an efficient way to correct the 3D aberration is to first apply ISAM processing to correct the 3D defocus and then apply CAO for en face plane images to correct the residual higher order aberrations.
In the current CAO using the Zernike polynomials method, manual adjustments to the coefficients was necessary, and an automated approach is currently under development. Although we have achieved a high acquisition rate for 3D cellular imaging by combing ISAM and CAO techniques, a faster processing rate is also very important, especially for medical diagnostics. Our group has succeeded in real-time ISAM and CAO using a guide star method by utilizing a graphics processing unit (GPU). Future work includes developing real-time CAO with automatically processing technique for various types of tissues. A recent publication, Ref. 34, using a sub-aperture correlation method to directly sense the aberration without knowing the parameters of system, is a good inspiration.
The authors thank Carle Foundation Hospital for providing access to the human tissue specimens used in this research. This research involving ex vivo human breast tissue and in vivo imaging in human subjects was conducted under Institutional Review Board protocols approved by the University of Illinois at Urbana-Champaign and Carle Foundation Hospital. We thank Eric Chaney for his assistance with managing these IRB protocols, Kush Paul and Ziad Mahmassani for providing the cell samples, and Darold Spillman for administrative and information technology support related to this research. We also thank the Imaging Technology Group in the Beckman Institute for Advanced Science and Technology for access to the computers used to process the data. This research was supported in part by grants from the National Institutes of Health (1 R01 EB012479, 1 R01 EB013723, and 1 R01 CA166309, S.A.B.). Additional information can be found at http://biophotonics.illinois.edu.
1. M. Rajadhyaksha, M. Grossman, D. Esterowitz, R. H. Webb, and R. R. Anderson, "In vivo confocal scanning laser microscopy of human skin: melanin provides strong contrast," J. Invest. Dermatol. 104(6), 946–952 (1995). [CrossRef] [PubMed]
2. Y. Zhao, B. W. Graf, E. J. Chaney, Z. Mahmassani, E. Antoniadou, R. Devolder, H. Kong, M. D. Boppart, and S. A. Boppart, "Integrated multimodal optical microscopy for structural and functional imaging of engineered and natural skin," J. Biophotonics 5(5-6), 437–448 (2012). [CrossRef] [PubMed]
3. D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, "Optical coherence tomography," Science 254(5035), 1178–1181 (1991). [CrossRef] [PubMed]
4. F. E. Robles, C. Wilson, G. Grant, and A. Wax, "Molecular imaging true-colour spectroscopic optical coherence tomography," Nat. Photonics 5(12), 744–747 (2011). [CrossRef] [PubMed]
5. J. A. Izatt, M. R. Hee, G. M. Owen, E. A. Swanson, and J. G. Fujimoto, "Optical coherence microscopy in scattering media," Opt. Lett. 19(8), 590–592 (1994). [CrossRef] [PubMed]
6. S. A. Boppart, B. E. Bouma, C. Pitris, J. F. Southern, M. E. Brezinski, and J. G. Fujimoto, "In vivo cellular optical coherence tomography imaging," Nat. Med. 4(7), 861–865 (1998). [CrossRef] [PubMed]
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9. R. Huber, M. Wojtkowski, J. G. Fujimoto, J. Y. Jiang, and A. E. Cable, "Three-dimensional and C-mode OCT imaging with a compact, frequency swept laser source at 1300 nm," Opt. Express 13(26), 10523–10538 (2005). [CrossRef] [PubMed]
10. M. Akiba and K. P. Chan, "In vivo video-rate cellular-level full-field optical coherence tomography," J. Biomed. Opt. 12(6), 064024 (2007). [CrossRef] [PubMed]
11. A. D. Aguirre, J. Sawinski, S.-W. Huang, C. Zhou, W. Denk, and J. G. Fujimoto, "High speed optical coherence microscopy with autofocus adjustment and a miniaturized endoscopic imaging probe," Opt. Express 18(5), 4222–4239 (2010). [CrossRef] [PubMed]
12. J. P. Rolland, P. Meemon, S. Murali, K. P. Thompson, and K. S. Lee, "Gabor-based fusion technique for optical coherence microscopy," Opt. Express 18(4), 3632–3642 (2010). [CrossRef] [PubMed]
13. B. A. Standish, K. K. C. Lee, A. Mariampillai, N. R. Munce, M. K. K. Leung, V. X. D. Yang, and I. A. Vitkin, "In vivo endoscopic multi-beam optical coherence tomography," Phys. Med. Biol. 55(3), 615–622 (2010). [CrossRef] [PubMed]
14. Z. Ding, H. Ren, Y. Zhao, J. S. Nelson, and Z. Chen, "High-resolution optical coherence tomography over a large depth range with an axicon lens," Opt. Lett. 27(4), 243–245 (2002). [CrossRef] [PubMed]
15. R. A. Leitgeb, M. Villiger, A. H. Bachmann, L. Steinmann, and T. Lasser, "Extended focus depth for Fourier domain optical coherence microscopy," Opt. Lett. 31(16), 2450–2452 (2006). [CrossRef] [PubMed]
16. L. Liu, C. Liu, W. C. Howe, C. J. R. Sheppard, and N. Chen, "Binary-phase spatial filter for real-time swept-source optical coherence microscopy," Opt. Lett. 32(16), 2375–2377 (2007). [CrossRef] [PubMed]
17. D. Hillmann, C. Lührs, T. Bonin, P. Koch, and G. Hüttmann, "Holoscopy--holographic optical coherence tomography," Opt. Lett. 36(13), 2390–2392 (2011). [CrossRef] [PubMed]
18. J. Mo, M. de Groot, and J. F. de Boer, "Focus-extension by depth-encoded synthetic aperture in optical coherence tomography," Opt. Express 21(8), 10048–10061 (2013). [CrossRef] [PubMed]
19. Y. Yasuno, J.-I. Sugisaka, Y. Sando, Y. Nakamura, S. Makita, M. Itoh, and T. Yatagai, "Non-iterative numerical method for laterally superresolving Fourier domain optical coherence tomography," Opt. Express 14(3), 1006–1020 (2006). [CrossRef] [PubMed]
20. L. Yu, B. Rao, J. Zhang, J. Su, Q. Wang, S. Guo, and Z. Chen, "Improved lateral resolution in optical coherence tomography by digital focusing using two-dimensional numerical diffraction method," Opt. Express 15(12), 7634–7641 (2007). [CrossRef] [PubMed]
21. A. Kumar, W. Drexler, and R. A. Leitgeb, "Numerical focusing methods for full field OCT: a comparison based on a common signal model," Opt. Express 22(13), 16061–16078 (2014). [CrossRef] [PubMed]
22. T. S. Ralston, D. L. Marks, P. S. Carney, and S. A. Boppart, "Interferometric synthetic aperture microscopy," Nat. Phys. 3(2), 129–134 (2007). [CrossRef]
23. T. S. Ralston, S. G. Adie, D. L. Marks, S. A. Boppart, and P. S. Carney, "Cross-validation of interferometric synthetic aperture microscopy and optical coherence tomography," Opt. Lett. 35(10), 1683–1685 (2010). [CrossRef] [PubMed]
24. B. J. Davis, S. C. Schlachter, D. L. Marks, T. S. Ralston, S. A. Boppart, and P. S. Carney, "Nonparaxial vector-field modeling of optical coherence tomography and interferometric synthetic aperture microscopy," J. Opt. Soc. Am. A 24(9), 2527–2542 (2007). [CrossRef] [PubMed]
25. D. L. Marks, B. J. Davis, S. A. Boppart, and P. Carney, "Partially coherent illumination in full-field interferometric synthetic aperture microscopy," J. Opt. Soc. Am. A 26(2), 376–386 (2009). [CrossRef] [PubMed]
26. D. L. Marks, T. S. Ralston, S. A. Boppart, and P. S. Carney, "Inverse scattering for frequency-scanned full-field optical coherence tomography," J. Opt. Soc. Am. A 24(4), 1034–1041 (2007). [CrossRef] [PubMed]
27. T. S. Ralston, D. L. Marks, P. S. Carney, and S. A. Boppart, "Real-time interferometric synthetic aperture microscopy," Opt. Express 16(4), 2555–2569 (2008). [CrossRef] [PubMed]
28. A. Ahmad, N. D. Shemonski, S. G. Adie, H. S. Kim, W. M. Hwu, P. S. Carney, and S. A. Boppart, "Real-time in vivo computed optical interferometric tomography," Nat. Photonics 7(6), 444–448 (2013). [CrossRef] [PubMed]
29. N. Ji, D. E. Milkie, and E. Betzig, "Adaptive optics via pupil segmentation for high-resolution imaging in biological tissues," Nat. Methods 7(2), 141–147 (2010). [CrossRef] [PubMed]
30. W. Lo, Y. Sun, S.-J. Lin, S.-H. Jee, and C.-Y. Dong, "Spherical aberration correction in multiphoton fluorescence imaging using objective correction collar," J. Biomed. Opt. 10(3), 034006 (2005). [CrossRef] [PubMed]
31. Y. Jian, R. J. Zawadzki, and M. V. Sarunic, "Adaptive optics optical coherence tomography for in vivo mouse retinal imaging," J. Biomed. Opt. 18(5), 056007 (2013). [CrossRef] [PubMed]
32. S. G. Adie, B. W. Graf, A. Ahmad, P. S. Carney, and S. A. Boppart, "Computational adaptive optics for broadband optical interferometric tomography of biological tissue," Proc. Natl. Acad. Sci. U.S.A. 109(19), 7175–7180 (2012). [CrossRef] [PubMed]
33. S. G. Adie, N. D. Shemonski, B. W. Graf, A. Ahmad, P. Scott Carney, and S. A. Boppart, "Guide-star-based computational adaptive optics for broadband interferometric tomography," Appl. Phys. Lett. 101(22), 221117 (2012). [CrossRef] [PubMed]
34. A. Kumar, W. Drexler, and R. A. Leitgeb, "Subaperture correlation based digital adaptive optics for full field optical coherence tomography," Opt. Express 21(9), 10850–10866 (2013). [CrossRef] [PubMed]
35. B. W. Graf, S. G. Adie, and S. A. Boppart, "Correction of coherence gate curvature in high numerical aperture optical coherence imaging," Opt. Lett. 35(18), 3120–3122 (2010). [CrossRef] [PubMed]
36. J. W. Goodman, Introduction to Fourier Optics, 3rd ed. (Roberts and Company Publishers, 2005).
37. S. G. Adie, B. W. Grafa, A. Ahmad, B. Dabarsyah, S. A. Boppart, and P. S. Carney, "The impact of aberrations on object reconstruction with interferometric synthetic aperture microscopy," Proc. SPIE 7889, 78891O (2011). [CrossRef]
38. S. Gabarda and G. Cristóbal, "Blind image quality assessment through anisotropy," J. Opt. Soc. Am. A 24(12), B42–B51 (2007). [CrossRef] [PubMed]
39. V. Lakshminarayanan and A. Fleck, "Zernike polynomials: a guide," J. Mod. Opt. 58(7), 545–561 (2011). [CrossRef]
40. J. R. Fienup and J. J. Miller, "Aberration correction by maximizing generalized sharpness metrics," J. Opt. Soc. Am. A 20(4), 609–620 (2003). [CrossRef] [PubMed]
41. G. Partadiredja, R. Miller, and D. E. Oorschot, "The number, size, and type of axons in rat subcortical white matter on left and right sides: a stereological, ultrastructural study," J. Neurocytol. 32(9), 1165–1179 (2003). [CrossRef] [PubMed]
42. B. W. Graf and S. A. Boppart, "Multimodal in vivo skin imaging with integrated optical coherence and multiphoton microscopy," IEEE J. Sel. Top. Quantum Electron. 18(4), 1280–1286 (2012). [CrossRef]
43. R. S. Gurjar, V. Backman, L. T. Perelman, I. Georgakoudi, K. Badizadegan, I. Itzkan, R. R. Dasari, and M. S. Feld, "Imaging human epithelial properties with polarized light-scattering spectroscopy," Nat. Med. 7(11), 1245–1248 (2001). [CrossRef] [PubMed]
44. P. Corcuff, C. Bertrand, and J. L. Leveque, "Morphometry of human epidermis in vivo by real-time confocal microscopy," Arch. Dermatol. Res. 285(8), 475–481 (1993). [CrossRef] [PubMed]
M. Rajadhyaksha, M. Grossman, D. Esterowitz, R. H. Webb, and R. R. Anderson, "In vivo confocal scanning laser microscopy of human skin: melanin provides strong contrast," J. Invest. Dermatol. 104(6), 946–952 (1995).
Y. Zhao, B. W. Graf, E. J. Chaney, Z. Mahmassani, E. Antoniadou, R. Devolder, H. Kong, M. D. Boppart, and S. A. Boppart, "Integrated multimodal optical microscopy for structural and functional imaging of engineered and natural skin," J. Biophotonics 5(5-6), 437–448 (2012).
D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, "Optical coherence tomography," Science 254(5035), 1178–1181 (1991).
F. E. Robles, C. Wilson, G. Grant, and A. Wax, "Molecular imaging true-colour spectroscopic optical coherence tomography," Nat. Photonics 5(12), 744–747 (2011).
J. A. Izatt, M. R. Hee, G. M. Owen, E. A. Swanson, and J. G. Fujimoto, "Optical coherence microscopy in scattering media," Opt. Lett. 19(8), 590–592 (1994).
S. A. Boppart, B. E. Bouma, C. Pitris, J. F. Southern, M. E. Brezinski, and J. G. Fujimoto, "In vivo cellular optical coherence tomography imaging," Nat. Med. 4(7), 861–865 (1998).
V. J. Srinivasan, H. Radhakrishnan, J. Y. Jiang, S. Barry, and A. E. Cable, "Optical coherence microscopy for deep tissue imaging of the cerebral cortex with intrinsic contrast," Opt. Express 20(3), 2220–2239 (2012).
J. A. Izatt, M. D. Kulkarni, K. Kobayashi, and M. V. Sivak, "Optical coherence tomography and microscopy in gastrointestinal tissues," IEEE J. Sel. Top. Quantum Electron. 2(4), 1017–1028 (1996).
R. Huber, M. Wojtkowski, J. G. Fujimoto, J. Y. Jiang, and A. E. Cable, "Three-dimensional and C-mode OCT imaging with a compact, frequency swept laser source at 1300 nm," Opt. Express 13(26), 10523–10538 (2005).
M. Akiba and K. P. Chan, "In vivo video-rate cellular-level full-field optical coherence tomography," J. Biomed. Opt. 12(6), 064024 (2007).
A. D. Aguirre, J. Sawinski, S.-W. Huang, C. Zhou, W. Denk, and J. G. Fujimoto, "High speed optical coherence microscopy with autofocus adjustment and a miniaturized endoscopic imaging probe," Opt. Express 18(5), 4222–4239 (2010).
J. P. Rolland, P. Meemon, S. Murali, K. P. Thompson, and K. S. Lee, "Gabor-based fusion technique for optical coherence microscopy," Opt. Express 18(4), 3632–3642 (2010).
B. A. Standish, K. K. C. Lee, A. Mariampillai, N. R. Munce, M. K. K. Leung, V. X. D. Yang, and I. A. Vitkin, "In vivo endoscopic multi-beam optical coherence tomography," Phys. Med. Biol. 55(3), 615–622 (2010).
Z. Ding, H. Ren, Y. Zhao, J. S. Nelson, and Z. Chen, "High-resolution optical coherence tomography over a large depth range with an axicon lens," Opt. Lett. 27(4), 243–245 (2002).
R. A. Leitgeb, M. Villiger, A. H. Bachmann, L. Steinmann, and T. Lasser, "Extended focus depth for Fourier domain optical coherence microscopy," Opt. Lett. 31(16), 2450–2452 (2006).
L. Liu, C. Liu, W. C. Howe, C. J. R. Sheppard, and N. Chen, "Binary-phase spatial filter for real-time swept-source optical coherence microscopy," Opt. Lett. 32(16), 2375–2377 (2007).
D. Hillmann, C. Lührs, T. Bonin, P. Koch, and G. Hüttmann, "Holoscopy--holographic optical coherence tomography," Opt. Lett. 36(13), 2390–2392 (2011).
J. Mo, M. de Groot, and J. F. de Boer, "Focus-extension by depth-encoded synthetic aperture in optical coherence tomography," Opt. Express 21(8), 10048–10061 (2013).
Y. Yasuno, J.-I. Sugisaka, Y. Sando, Y. Nakamura, S. Makita, M. Itoh, and T. Yatagai, "Non-iterative numerical method for laterally superresolving Fourier domain optical coherence tomography," Opt. Express 14(3), 1006–1020 (2006).
L. Yu, B. Rao, J. Zhang, J. Su, Q. Wang, S. Guo, and Z. Chen, "Improved lateral resolution in optical coherence tomography by digital focusing using two-dimensional numerical diffraction method," Opt. Express 15(12), 7634–7641 (2007).
A. Kumar, W. Drexler, and R. A. Leitgeb, "Numerical focusing methods for full field OCT: a comparison based on a common signal model," Opt. Express 22(13), 16061–16078 (2014).
T. S. Ralston, D. L. Marks, P. S. Carney, and S. A. Boppart, "Interferometric synthetic aperture microscopy," Nat. Phys. 3(2), 129–134 (2007).
T. S. Ralston, S. G. Adie, D. L. Marks, S. A. Boppart, and P. S. Carney, "Cross-validation of interferometric synthetic aperture microscopy and optical coherence tomography," Opt. Lett. 35(10), 1683–1685 (2010).
B. J. Davis, S. C. Schlachter, D. L. Marks, T. S. Ralston, S. A. Boppart, and P. S. Carney, "Nonparaxial vector-field modeling of optical coherence tomography and interferometric synthetic aperture microscopy," J. Opt. Soc. Am. A 24(9), 2527–2542 (2007).
D. L. Marks, B. J. Davis, S. A. Boppart, and P. Carney, "Partially coherent illumination in full-field interferometric synthetic aperture microscopy," J. Opt. Soc. Am. A 26(2), 376–386 (2009).
D. L. Marks, T. S. Ralston, S. A. Boppart, and P. S. Carney, "Inverse scattering for frequency-scanned full-field optical coherence tomography," J. Opt. Soc. Am. A 24(4), 1034–1041 (2007).
T. S. Ralston, D. L. Marks, P. S. Carney, and S. A. Boppart, "Real-time interferometric synthetic aperture microscopy," Opt. Express 16(4), 2555–2569 (2008).
A. Ahmad, N. D. Shemonski, S. G. Adie, H. S. Kim, W. M. Hwu, P. S. Carney, and S. A. Boppart, "Real-time in vivo computed optical interferometric tomography," Nat. Photonics 7(6), 444–448 (2013).
N. Ji, D. E. Milkie, and E. Betzig, "Adaptive optics via pupil segmentation for high-resolution imaging in biological tissues," Nat. Methods 7(2), 141–147 (2010).
W. Lo, Y. Sun, S.-J. Lin, S.-H. Jee, and C.-Y. Dong, "Spherical aberration correction in multiphoton fluorescence imaging using objective correction collar," J. Biomed. Opt. 10(3), 034006 (2005).
Y. Jian, R. J. Zawadzki, and M. V. Sarunic, "Adaptive optics optical coherence tomography for in vivo mouse retinal imaging," J. Biomed. Opt. 18(5), 056007 (2013).
S. G. Adie, B. W. Graf, A. Ahmad, P. S. Carney, and S. A. Boppart, "Computational adaptive optics for broadband optical interferometric tomography of biological tissue," Proc. Natl. Acad. Sci. U.S.A. 109(19), 7175–7180 (2012).
S. G. Adie, N. D. Shemonski, B. W. Graf, A. Ahmad, P. Scott Carney, and S. A. Boppart, "Guide-star-based computational adaptive optics for broadband interferometric tomography," Appl. Phys. Lett. 101(22), 221117 (2012).
A. Kumar, W. Drexler, and R. A. Leitgeb, "Subaperture correlation based digital adaptive optics for full field optical coherence tomography," Opt. Express 21(9), 10850–10866 (2013).
B. W. Graf, S. G. Adie, and S. A. Boppart, "Correction of coherence gate curvature in high numerical aperture optical coherence imaging," Opt. Lett. 35(18), 3120–3122 (2010).
J. W. Goodman, Introduction to Fourier Optics, 3rd ed. (Roberts and Company Publishers, 2005).
S. G. Adie, B. W. Grafa, A. Ahmad, B. Dabarsyah, S. A. Boppart, and P. S. Carney, "The impact of aberrations on object reconstruction with interferometric synthetic aperture microscopy," Proc. SPIE 7889, 78891O (2011).
S. Gabarda and G. Cristóbal, "Blind image quality assessment through anisotropy," J. Opt. Soc. Am. A 24(12), B42–B51 (2007).
V. Lakshminarayanan and A. Fleck, "Zernike polynomials: a guide," J. Mod. Opt. 58(7), 545–561 (2011).
J. R. Fienup and J. J. Miller, "Aberration correction by maximizing generalized sharpness metrics," J. Opt. Soc. Am. A 20(4), 609–620 (2003).
G. Partadiredja, R. Miller, and D. E. Oorschot, "The number, size, and type of axons in rat subcortical white matter on left and right sides: a stereological, ultrastructural study," J. Neurocytol. 32(9), 1165–1179 (2003).
B. W. Graf and S. A. Boppart, "Multimodal in vivo skin imaging with integrated optical coherence and multiphoton microscopy," IEEE J. Sel. Top. Quantum Electron. 18(4), 1280–1286 (2012).
R. S. Gurjar, V. Backman, L. T. Perelman, I. Georgakoudi, K. Badizadegan, I. Itzkan, R. R. Dasari, and M. S. Feld, "Imaging human epithelial properties with polarized light-scattering spectroscopy," Nat. Med. 7(11), 1245–1248 (2001).
P. Corcuff, C. Bertrand, and J. L. Leveque, "Morphometry of human epidermis in vivo by real-time confocal microscopy," Arch. Dermatol. Res. 285(8), 475–481 (1993).
Adie, S. G.
Aguirre, A. D.
Akiba, M.
Anderson, R. R.
Antoniadou, E.
Bachmann, A. H.
Backman, V.
Badizadegan, K.
Barry, S.
Bertrand, C.
Betzig, E.
Bonin, T.
Boppart, M. D.
Boppart, S. A.
Bouma, B. E.
Brezinski, M. E.
Cable, A. E.
Carney, P.
Carney, P. S.
Chan, K. P.
Chaney, E. J.
Chang, W.
Chen, N.
Chen, Z.
Corcuff, P.
Cristóbal, G.
Dabarsyah, B.
Dasari, R. R.
Davis, B. J.
de Boer, J. F.
de Groot, M.
Denk, W.
Devolder, R.
Dong, C.-Y.
Drexler, W.
Esterowitz, D.
Feld, M. S.
Fienup, J. R.
Fleck, A.
Flotte, T.
Fujimoto, J. G.
Gabarda, S.
Georgakoudi, I.
Graf, B. W.
Grafa, B. W.
Grant, G.
Gregory, K.
Grossman, M.
Guo, S.
Gurjar, R. S.
Hee, M. R.
Hillmann, D.
Howe, W. C.
Huang, D.
Huang, S.-W.
Huber, R.
Hüttmann, G.
Hwu, W. M.
Itoh, M.
Itzkan, I.
Izatt, J. A.
Jee, S.-H.
Ji, N.
Jian, Y.
Jiang, J. Y.
Kim, H. S.
Kobayashi, K.
Koch, P.
Kong, H.
Kulkarni, M. D.
Kumar, A.
Lakshminarayanan, V.
Lasser, T.
Lee, K. K. C.
Lee, K. S.
Leitgeb, R. A.
Leung, M. K. K.
Leveque, J. L.
Lin, C. P.
Lin, S.-J.
Liu, L.
Lo, W.
Lührs, C.
Mahmassani, Z.
Makita, S.
Mariampillai, A.
Marks, D. L.
Meemon, P.
Milkie, D. E.
Miller, J. J.
Miller, R.
Mo, J.
Munce, N. R.
Murali, S.
Nakamura, Y.
Nelson, J. S.
Oorschot, D. E.
Owen, G. M.
Partadiredja, G.
Perelman, L. T.
Pitris, C.
Puliafito, C. A.
Radhakrishnan, H.
Rajadhyaksha, M.
Ralston, T. S.
Rao, B.
Ren, H.
Robles, F. E.
Rolland, J. P.
Sando, Y.
Sarunic, M. V.
Sawinski, J.
Schlachter, S. C.
Schuman, J. S.
Scott Carney, P.
Shemonski, N. D.
Sheppard, C. J. R.
Sivak, M. V.
Southern, J. F.
Srinivasan, V. J.
Standish, B. A.
Steinmann, L.
Stinson, W. G.
Su, J.
Sugisaka, J.-I.
Sun, Y.
Swanson, E. A.
Thompson, K. P.
Villiger, M.
Vitkin, I. A.
Wang, Q.
Wax, A.
Webb, R. H.
Wilson, C.
Wojtkowski, M.
Yang, V. X. D.
Yasuno, Y.
Yatagai, T.
Yu, L.
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(1) S ˜ ˜ ˜ ( q x , q y , k ) = H ( q x , q y , k ) η ˜ ˜ ˜ [ q x , q y , − ( 2 k ) 2 − ( q x 2 + q y 2 ) ] ,
(2) η ˜ ˜ ˜ + ( q x , q y , q z ) ≈ S ˜ ˜ ˜ ( q x , q y , k ) | k = 1 2 q z 2 + q x 2 + q y 2
(3) η ( x , y , z ) = F − 1 [ η ˜ ˜ ˜ + ( q x , q y , q z ) ]
(4) S ˜ ˜ ˜ A ( q x , q y , k ) = H A ( q x , q y , k ) H ( q x , q y , k ) η ˜ ˜ ˜ [ q x , q y , − ( 2 k ) 2 − ( q x 2 + q y 2 ) ]
(5) S ˜ ˜ ˜ A C ( q x , q y , k ) = H A C ( q x , q y , k ) S ˜ ˜ ˜ A ( q x , q y , k )


Sample Follow-up letter after business proposal. Extending business is a form of expansion in the arcade of businesses. Contracts are crucial in binding an agreement between two business groups, but follow up is a key to success and a civic right of either party to let knowledge of acceptance or rejection. This format can fulfill the need of the person sitting in the agreement.
I hope good will and health at your side. I am writing this piece of inscription as a reminder of my proposal that I offered you at the meeting held in Seven Star Hotel. In the meeting, I gave you the idea of patching up an agreement between us on shared basis. I offered an idea of crafting the steel in the modern equipment as major out-break in the chain of businesses world! You were quite inspired from my proposal and suggested me to inform you as follow up of my business proposal as soon as possible. I am now here with my pledge and firm words.
I am new in this field, but I have high aims and ample career knowledge of how to turn mud into pottery. I assure you that I will not be a proven mistake if you show your trust on me by giving me the chance of entering in the era of businesses. I will learn to excel from you as far as I can live my life. Kindly reply me back so that I can see you at my earliest and start this new exciting venture with your learned self. I am yearning to hear a positive reply from you.


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text:
Ann Arbor Give Camp
jennmar July 15, 2008 13
I am truly fortunate to be part of such an amazing developer community! I am still reeling from the passion that I experienced at the Ann Arbor Give Camp last weekend.
The Ann Arbor Give Camp was a weekend-long codefest where developers, designers, and DBAs volunteered their time to create websites and applications for non-profit organizations. The event was held at the Washtenaw Community College, who generously donated the cost of the venue. Verio donated free hosting until January 2010 to all of the non-profit organizations, and even sent a technical resource, the amazing Matt Lagrotte, onsite to make sure that the accounts were set up properly.
We kicked off the event on Friday night at 6pm; each charity spoke briefly about their mission statement and their technology needs. On Sunday at 3pm, we held the closing presentation where the developers were able to demonstrate their work.
There were many different projects. Multiple charities had no web presence and needed their very first website. One charity needed a volunteer management system, and the development team led by Jeff McWherter created a generic web-based scheduling application that allows volunteers to schedule themselves to work events for a nonprofit organization (they posted it to CodePlex, Microsoft's open source project hosting web site, so that any organization can access and use it). The Michigan Humane Society needed a searchable database to make it easier to find animals. To give you an idea of the scope of the problem: in 2007, 104,690 dogs were surrendered to registered animal shelters. Only 19,151 were returned to their owners. This searchable database could allow pet owners to more easily find their lost pets, and assist individuals who find stray animals find the appropriate location for stray holding. It's really amazing to see such concrete examples of technology enpowering people!
In total, we were able to help 15 charities:
• Michigan Chapter of the National Children's Alliance
• Michigan Humane Society
• The Wellness Community
• Caring Alternatives, Inc.
• Forgotten Harvest
• Ann Arbor Hands-On Museum
• Angel's Place
• Wonder Puzzle
• Child Care Network
• Golightly Academy of IT
• The Information Center
• Center Stage Drama
• Arab American Culture Center
• SDL EQ Enrichment Center
• NOCIRC Michigan
The Give Camp actually happened at a very opportune time, since last week Microsoft just launched a portal for non-profit organizations at http://www.microsoft.com/NGO. This is a wonderful resource; it contains stories of charities using technology, discussion forums, access to free or discounted software and hardware, software support, and training and certification opportunities.
How do I summarize the magic of the weekend? It was absolutely inspirational to watch. The developers and designers were so passionate about their charities. A ripple effect occurred, where one developer would realize that he/she had a friend with particular skills to assist with some problem, call up the friend, and then the friend would come and code with us too! There were 85 registered developers/designers that I knew of who attended, but we quickly lost track of everyone coming in and out - there were roughly 100 people total who volunteered.
There were also people participating from two remote locations - the Columbus, OH effort was led by Carey Payette and my teammate Jeff Blankenburg, and the Knoxville, TN effort was led by Nathan Blevins.
I got maybe 6 hours of sleep the entire weekend, but it was worth it! We were crunching some numbers (cost of developer time, Verio hosting, software donations, etc.), and figured out that this event provided about a half million dollars in goods and services to these charities!!!
Huge thanks to my fellow organizers: Patrick Steele, John Hopkins, Todd Bohlen, Bill Wagner, and Kristina Jones. These people are wonderful to work with, and it was an incredible team effort to make the event happen. We also had some phenomenal people step up during the event and make everything run smoothly: thank you Josh Holmes, Michael Eaton, and Greg Campeau.
This event also wouldn't have been possible without the donations from our generous sponsors. Financial support and services were provided by Microsoft, Verio, Washtenaw Community College, SRT Solutions, Infragistics, Telerik, TechSmith, and DevMavens by Lake Quincy Media. Food was donated by Domino's Pizza, Arbor Brewing Company, Dunkin' Donuts, Aubree's Pizza, Busch's, and Trader Joe's. Software was donated by Microsoft, Infragistics, and Telerik.
Here are links to other writeups on the event (if you blogged about it and I haven't mentioned you, let me know and I will add you):
Nathan Blevins
Sarah Dutkiewicz
Michael Eaton
Mark Gilbert
Josh Holmes
Michael Luttenberger
Wally McClure
John Mullinax
Michael Neel
Philip Presson
Martin Shoemaker
Patrick Steele
Mike Woelmer
Again, THANK YOU to everyone who participated!
Tags Ann Arbor Give Camp
a-foton » Ann Arbor Give Camp says:
PingBack from http://blog.a-foton.ru/2008/07/ann-arbor-give-camp/
Matt Lagrotte says:
Thanks for the kind words. Give camp rocked! Can't wait to see you all at the next one!
Scott Orwig says:
I'm bummed I had to miss Give Camp. Looks like it was fun AND rewarding. As a father of four with two newborns, though, I just couldn't get away for a whole weekend.
My (almost certainly unpopular) request would be to hold the next one during set daytime hours. But then I suppose it wouldn't be as fun for most of the attendees. I think maybe I'm just not in a "fun" demographic at the moment.
Congrats and thank you to all who put in the time.
Steven James says:
Scott:
Good news. You can even work from home. I was there and my neighbor could not make it in. He instead worked from his house. You can also come anytime to this event, day or night. Jennifer, thanks for your help and thank all the others who work there this weekend. Go VERIO and Go Domino's and GO MICROSOFT. Thanks to all the other sponcers too….
Steven James, AKA "The Nerd".
ViNull, Off the Record says:
This past weekend Knoxville took part in the Ann Arbor Give Camp thanks to Nathan Blevins .  Nathan
SRT Insights says:
Ann Arbor Give Camp started with Jennifer Marsman , of Microsoft, wanting to organize an event to pull
That's really great to hear. What an awesome event and my thanks go out to everyone who organized, sponsored, and participated in this.
Kevin Swiber says:
Awesome job. Let me know if another Give Camp sprouts. Even if it's not nearby, I'd be willing to join a satellite team.
Blog: http://kevinswiber.com/go/developer-community/ann-arbor-give-camp-2008/
See ya at the next GANG meeting!
Chris Koenig says:
Congratulations to Jennifer Marsman and the team running the Ann Arbor GiveCamp event last weekend.
ChrisKoenig says:
MSDN Blogs says:
Jennifer Marsman says:
I haven't blogged in awhile (other than "come to this event" posts, which don't count).
dunkin donuts coupons 2012 says:
http://www.getdunkindonutscoupons.com/dunkin-donuts-coupons-2012
Windows Webcasts Upcoming Events Windows Azure Windows Store Machine Learning Conferences Internet Explorer Featured Women in Tech Windows Phone Visual Studio Give Camp Parallel Programming Ann Arbor Women in Tech Artificial Intelligence Multitouch Apps .NET Cloud Computing

redpajama_set_name: RedPajamaCommonCrawl


text:
Q: inside iframe which embeded in light switch screen, how to call java script function from the parent custom control element? if i have 2 HTML pages and i embed on of them (child page) inside the other(parent page) using iframe i can call function js function in the child from the parent using
window.parent.myfunction();

note: don't work on chrome
i need to apply this in visual studio light switch
i embed HTML page inside custom control element in light switch screen using iframe and i want to call JavaScript function from the custom control render to use it whit a button inside the iframe (onclick) .. i tried    window.parent.myfunction(); but it didn't work.
the custom control render
myapp.LaunchURL.BigCustom_render = function (element, contentItem) {

    element.innerHTML += '

"';
    document.getElementById("mycontent").innerHTML +=
       '';

    var iframe = $('iframe').contents();

    iframe.find('#h2id').text("change the text please");

    iframe.find('#A2').attr("value", "ok this works");

    myapp.activeDataWorkspace.ApplicationData.Students.load().then(
        function onComplete(result) {
            var studentNames = "";
            result.results.forEach(function (student) {
                //alert(student.Name);
                studentNames += (student.Name + " ");
            });

           // alert(studentNames);

            iframe.find('#A1').attr("type", "text");
            iframe.find('#A1').attr("value", studentNames);
        }
        );

    function AlertOnChange()
    {

        alert("the student name changes");
    }

    //to have the entire webpage
    $("iframe").parent().parent().css("width", "100%");
    $("iframe").parent().parent().css("height", "1200px");

    //to eliminate the header if you want to
    $("span").parent().parent().parent().parent().parent().css("width", "0px");
    $("span").parent().parent().parent().parent().parent().css("height", "0px");

};

the HTML page
<!DOCTYPE html>

    <title>Dating Form</title>

 the students

    <form>

        <input type="button" value="Get Students" onclick="window.parent.AlertOnChange();"></input>

        <input type="hidden" id="A1" name="A1" value="hidden" onchange="window.parent.AlertOnChange()"> Students Names </input>

        <input type="text" id="A2" name="A2" value="text this text box"> textbox </input>

    </form>

this button doesn't respond and doesn't do eny thing

A: i defined the function outside the custom control render and it works
this is my code
var AppData;

myapp.LaunchURL.BigCustom_render = function (element, contentItem) {

    element.innerHTML += '

"';
    document.getElementById("mycontent").innerHTML +=
       '';

    var iframe = $('iframe').contents();

    iframe.find('#h2id').text("change the text please");

    iframe.find('#A2').attr("value", "ok this works");

    //to have the entire webpage
    $("iframe").parent().parent().css("width", "100%");
    $("iframe").parent().parent().css("height", "1200px");

    //to eliminate the header if you want to
    $("span").parent().parent().parent().parent().parent().css("width", "0px");
    $("span").parent().parent().parent().parent().parent().css("height", "0px");

};

function AlertOnChange() {
    alert("the student name changes");

    AppData.Students.load().then(
    function onComplete(result) {
        var studentNames = "";
        result.results.forEach(function (student) {
            //alert(student.Name);
            studentNames += (student.Name + " ");
        });

        // alert(studentNames);
        alert(studentNames);
        $('iframe').contents().find('#A1').attr("type", "text");
        $('iframe').contents().find('#A1').attr("value", studentNames);
    }
    );

}

myapp.LaunchURL.created = function (screen) {
    // Write code here.
    AppData = myapp.activeDataWorkspace.ApplicationData;
};

redpajama_set_name: RedPajamaStackExchange


text:
The Language of Resilience
Posted on April 18, 2018 by John Richardson
Maha Sukkar, a senior constable from Victoria Police, opened this session speaking in Arabic, giving people directions and making people feeling uncomfortable and uncertainty, because they did not understand what she was saying. She brilliantly illustrated the point that language, in situations of high stress is important.
Penny Egan-Vine spoke about the issues that face refugees is a political label, ie crossing the border legitimately. Refugees need a sense of safety, and this can stay with them for some time, as they have lost everything previously. They may also suffer from trauma, but this is a small proportion. The challenge for disaster managers to make sure how a sense of safety can be restored, for everyone.
Scott Hanson-Easey, from Adelaide University spoke about the use of language, and commented on the development of fact sheets. If they aren't informed by communities, then they aren't useful. Translations can be problematic. Some words don't translate well. Language offers us concepts and frames for experiencing the world around us. Not universal. Australians come form all over the globe, but their experience of risk. Concepts are images that are then formed into language, it gives us a common code, we we can discuss and debate issues and risks and their solutions. Wittgenstein said, the limits of my language are the limits of my world.
Using a community-based participatory research, used a co-learning approach with the Karen community in Nhill. The approach built on their strengths, they wanted a film to reflect what to do and not to with fire restrictions.
Next we heard of research from Tasmania, by Isabelle Bartkowiak-Theron, focusing on training for police to work with refugees, recognising that people in uniform are perpetrators in many refugee's experiences. Many community members will be looking to contribute and help. Trust is important, and there needs to be a shared language between organsiations.
By a prerecorded presentation, we heard from Shefali Juneja Lakhina who related the experience of a family that arrived in Australia, from a terribly traumatic experience in northern Iraq. While being put into a beach cabin, which appeared nice, but for the family, it felt unsafe, as none of the family could swim. A severe storm made them very anxious, and their case manager suggested calling 000. But they felt as though they couldn't call them. Refugees are unaware of the natural hazard risk
A project that she coordinated, using a resilient personal mapping tool, identified the needs of newly arrived refugees. There were five recommendations
Provide systematic access to hazard and risk information
Ensure access to safe secure healthy housing
Priorities in home preparedness
Integrate resilience planning across sectors
Adopt person centered approaches to co-learning.
She also spoke about the Co-learning disaster resilience toolkit, which she developed
Asylum seekers as a group were also identified as one particularly most at risk, and difficult to know how to engage with. I highlighted the great work that our Queensland guys have done with asylum seekers.
https://publications.iom.int/books/migrants-disaster-risk-reduction-practices-inclusion
2 thoughts on "The Language of Resilience"
Amanda Lamont says:
I was asked today if I was going to translate the national disaster resilience glossary into all the languages of the Australian indigenous people.
John Richardson says:
How cool. But. Which ones? And will all terms translate!!!


text:
What is the Mars Explorer Program? (coming soon)
Are you an educator, a student of science, an aspiring young astronaut or just curious about Mars?
The Mars Explorer Program is an initiative by the Mars Society of Canada to develop an open-source,
accessible and enjoyable online learning space on the subject of Mars exploration.
We are generating curricula with the objective of providing a foundational understanding of subjects such as:
The History of Space Exploration to Mars
The Possible Future of Mars Exploration
Education and Career Paths for Aspiring Mars Explorers
An Overview of Key Scientific Mars Discoveries
Essential Mars and Space Exploration Facts in Physics, Chemistry, Engineering, Biology and more
Profiles of Key Organizations and Professionals in Mars Exploration
Are you an educator with experience in e-learning and a passion for space exploration?
Contact us if you would like to support the development of this program!
Follow us on social media for updates on Mars Explorer and more!
You can be a part of the path to Mars!
We depend on our membership to make efforts like the Mars Explorer Program possible. Become a member of the Mars Society of Canada, and support our not-for-profit initiatives like this and others!


text:
Big Brother Season 25 Release Date: Does It Have Returning Houseguests?
Big Brother Season 25 Release Date: The upcoming premiere of Big Brother 25 is much-discussed, and we have you covered. Read this article to learn everything there is to know about Big Brother 25. Since 2000, Big Brother has been a popular reality competition program in the United States.
One can infer that the show must have a large audience and undoubtedly rank among the top favorite shows of the public if it has lasted this long. When we say that the show has been a massive hit since its premiere, we are not exaggerating. We owe the CBS network a debt of gratitude for airing this enjoyable program.
Big Brother is a television program about a group of strangers from the United States who are abandoned on an island and forced to live in seclusion. There is a lot of diversity in the house each year. The struggle of everyone from all cultures and nationalities to get along makes the program so great. With its hilarious games and startling word challenges, it is rife with humor.
Big Brother gives viewers a fresh perspective on life by demonstrating how strangers would cooperate or make each other's lives miserable in exchange for money. Julie Chen Moonves has been hosting the program since its premiere in 2000. People would not have anyone else for the part because of her excellent hosting. The biggest issue is when Big Brother 25 will air on CBS. Find out by continuing to read!
Big Brother Season 25 Release Date
We assume Big Brother Season 25 won't be available to stream as of September 28, 2022, as revealed by Julie Chen on Twitter. Midway through 2023, or sometime around next summer, the series is anticipated to debut. But if we had to make a wild prediction, the 25th season might air from May to July 2023.
Big Brother 25 is expected to air on Sunday, Wednesday, and Thursday nights. We want to make clear that the month is simply a prediction at this time; CBS will reveal the precise release date when the month gets closer to the official release.
However, since the network's official social media accounts have not yet made the series' premiere date official, there is a lot of speculation among fans. This is because viewers know that the episodes will need time to be perfected during the production and post-production stages to make the upcoming season much more engaging.
As a result, we advise fans to be patient as these announcements take some time to disseminate and are made by the network and streaming providers on a schedule.
Why Was Big Brother Renewed for Another Season?
Since the start of season 24 on July 6, 2022, viewers have spent more than 11.56 billion minutes watching Big Brother on the CBS Television Network, Paramount+, and CBS.com/the CBS app, according to statistics from Nielsen linear viewership and Paramount internal data.
After The Events Of "Chainsaw Man" Who Does Denji End Up With? Explained
According to the research, "Big Brother material leads all streaming platforms in interaction, including the most recent season of the smash hit Stranger Things on Netflix. According to Nielsen Streaming Data from 7/6/22 to 9/18/22, 8.99 billion minutes were watched. The summer's top primetime show for adults 25-54 was Big Brother on Wednesday and Thursday, with Sunday shows tying for third place. The three evening programs ranked within the top 10 regarding viewers and adults 25–54.
Who Will Be Part of The Big Brother Season 25 Cast?
We know the original Julie Chen Moonves will also serve as the season's host. We'll soon learn more about the contestants, though. The following is a list of those who participated in Season 24:
Alyssa Snider
Daneil Durston
Ameerah Jones
Joseph Abdin
Indy Santos
Jasmine Davis
Monte Taylor
Taylor Hale
Joe Pooch Pucciarelli
Our girl won #BB24 and made #BigBrother history! Talk about raising Hale 🥲 Hear Taylor Hale's story and advice for future houseguests here. pic.twitter.com/7zDOLSVhyY
— Big Brother (@CBSBigBrother) September 28, 2022
What Will Be The Plot Of Big Brother Season 25?
A residence can have a staggering number of visitors, and they will evict one another every week. A strange idea, but that's how this program operates. Participants are not allowed to take their mics off or use the restroom. Furthermore, no one will be expelled for participating in the bed scene; on the contrary, they are all invited. Someone is interested in sexual activity since he liked one of the home guests.
#BB24 might be coming to a close, but Season 25 is just on the horizon. 😎 Never forget: expect the unexpected. https://t.co/XnaV3L5vw1
Others attempt to win the attention of other guests by using their bodies. They have little choice but to give up to more vigorous opponents to hold out for longer. They list individuals who don't want to share a table or live in the same rooms behind each other's backs.
Who is The Host of Big Brother Season 25?
Big Brother 25 will presumably be hosted by Julie Chen Moonves, who has done so since the program's debut in 2000. She formerly appeared on The Early Show, CBS This Morning, and CBS Morning News. She has an outstanding experience as a CBS anchor and talk show host. She and Les Moonves, the former CEO of CBS who left in 2018, were The Talk's moderator and co-host from 2010 until 2018.
Who Won Big Brother 24?
Taylor Hale's transformation from a house pariah who endured weeks of verbal abuse and was almost ousted in Week One to sitting in the final two chairs during Season 24 was a tale for the ages. She defeated Monte Taylor in the social game and story category with almost overwhelming support from the judges.
As the first Big Brother winner who also took home the title of America's Favorite Houseguest, Taylor made history as the first Black woman to win the competition.
We worked hard on this post, and we hope you enjoy it. Please let us know your thoughts in the comments below if this is the case. If you want to keep up with this kind of news, you should add Journalistpr.com. to your favorites.
1 Big Brother Season 25 Release Date
2 Why Was Big Brother Renewed for Another Season?
3 Who Will Be Part of The Big Brother Season 25 Cast?
4 What Will Be The Plot Of Big Brother Season 25?
5 Who is The Host of Big Brother Season 25?
6 Who Won Big Brother 24?


I have noticed that an interpreter that I team with nearly every week (she has been an interpreter for over 20 years, and trust me, she never lets me forget it for one minute) tends to omit information. Either she doesn't think it's important, or she just doesn't understand it herself. Forget suggesting giving her "feeds" from me, I've "only" been nationally certified for 5 years, and still am a baby in her book. My problem is that she always asks me to do team interpreting assignments with her, and asks for nobody else. I know you're going to tell me to say something to her, but our community is so small I can't afford to anger her, financially or professionally. How can I handle this?
Your situation might not have the negative conclusion you seem to fear. There is no reason at this point to think that saying something to her will anger her. Start by telling her that you have noticed that she omitted "xyz." Be specific. It is possible she has legitimate reasons for omitting certain information. Give her a chance to explain herself. For example, there are legitimate reasons why someone interpreting a "how to" computer software class will not sign everything a chatty trainer might say. You may get the opportunity to see something from a different perspective. If, however, it is as you infer - that she is omitting valuable material - ask for her perspective in a positive way that does not put her on the defensive and indeed make her angry at you. Choose to say something like, "What leads you not to include that?" instead of asking her a defensive question like, "Why are you leaving that material out?" Depending on her answer you may have to make a choice of how much you want to work with her or what else you might say or do.
I had to fight and advocate for ten weeks to have an interpreter replaced in a team setting during a 15 week graduate class. The supervisor of interpreters finally came and observed the interpreter's skills and agreed that in spite of her certification and years of experience, her skills were indeed inadequate in that particular setting. Had her team interpreter reported her, I would not have had to go through ten weeks of missing valuable classroom information and weeks spent advocating on my own. The supervisor was in fact reluctant to replace the interpreter because of her years of experience and because the team interpreter never said anything.
I believe the team interpreter had a responsibility to give feedback to her colleague and peer about what was lacking. Interpreters are responsible for communication the whole time they are on the job not just during their "shift." Once an interpreter is out in the field, there is no other monitoring system other than peers in team situations. Interpreters shouldn't worry about angering the other interpreter, but focus on communication that the Deaf person may not be getting that could result in failing a test, not getting a promotion, or any number of other negative consequences.
I interpret in a technology class where I am the only female in the room. The students often make crude remarks about women and the class always looks over at me and cracks up while I interpret them. I can see my Deaf client is embarrassed for me, but he laughs along with the rest of them.
In any classroom, the teacher bears responsibility for controlling student behavior, whether it's kindergarten or graduate school. I would approach this problem as a discipline issue. If you talk about this issue by placing the focus on yourself - on how you feel or how this behavior is hurting you - statements like that leave room for others to suggest that you are too sensitive, or that "boys will be boys." Instead, talk about the class behavior in terms of outcome: it is disruptive, impedes the student's access to instructional material, and impedes the interpreting process. Use words that carry legal impact.
Always talk to the teacher first. The field of education is fraught with politics, and it is better to begin the problem solving process in the classroom. If that fails, then the next step is to ask to talk to your immediate supervisor (not the teacher's). Your supervisor should handle the matter from there. Be clear in what you expect. I would ask my supervisor to have the classroom discipline issue dealt with. If that doesn't resolve the issue, I would then ask my supervisor to move me to another class, since I cannot perform effectively in a hostile work environment.
In a perfect world, the deaf client will speak up in the interpreter's defense and scold the class for making crude remarks about women in general, and specifically you, the interpreter. But in today's real world, the way to handle this is for the female interpreter to lodge a formal protest with the teacher about the boorish behavior of the class (including the deaf client who laughed along with the rest of them). Hopefully, the teacher will be able to handle this situation. However, if the teacher is not able to do so, then file a harassment complaint. Why? We do have harassment laws and if we do not invoke on those laws protecting people, harassment of any form or substance will continue to no end. It is high time to make our laws work so that we can all live in a perfect world.
I completely agree with the "Experienced Deaf Consumer's Perspective."
I've worked in higher education for over 20 years, and the statement that "education is fraught with politics" is very true. But that doesn't mean you should let sexual harassment stand. If you transfer to a different classroom without making a formal complaint, you are enabling the problem to continue, and teaching all the students (and the teacher, too) that sexual harassment is ok. Definitely talk to the teacher first -- but don't let it continue.


Microsoft to Buy Yahoo? Oh No They Didn't!
File this one under: Snap, Oh.
Remember how everyone was all like, "yo, Microsoft, you totally like Yahoo?" Yeah? Well, now Microsoft's like, "Nuh-uh, I don't need that sucka, Yahoo!, I gots all the pieces to make my own ad business, fool."


Take your managers through 'a year in a day' of managing performance!
Using video clips, email trails and others clues, delegates interact with two fictional team members. Over months, a minor issue becomes a major performance management challenge. At every stage delegates are invited to intervene and address the performance issues. Just like real life, the longer they leave it…the worse it gets!
The day culminates in delegates giving both team members an appraisal.
With this refreshingly different approach, delegates are drawn into the reality of managing performance all year round, not just at appraisal time.
One-day workshop for up to 25 managers.
Contact us by email or by phone 01491 411544 for prices and availability.


9a-11a - Darrel Willis, Acoustic guitar pop songs and blues.
11a-1p - Carol Beswick, Folk, rock, blues & even a few kids tunes come together on ukulele & guitar.
Saturday Book Sale - Come by the library every Saturday, from 11-2p, for weekly Friends of the Mt. Pleasant Library book sales. The Friends room is up on the 2nd floor across from the entrance to the Children's Room.


Munch sent me this picture, mentioned on the "Hertford memories"
from Munch's email. Hey... spooky! Select a book at random from the pile I've inherited from my godmother, open it and it's a picture of a London CH dormitory!
Is it a woodcut? Or an etching? Not sure! Anyway, some Forumites might like to see it, or may be able to date it? The book is "The Victorian Scene: 1837-1901" by Nicholas Bentley, 1968.
Interesting. Shows a ward with, presumably 50 beds and settles.
The boys do not have full length coats, and their bands are awry.
La Touche (1868) shows bands neatly overlying one another.
The ward looks like one of 1823, rather than the later one of 1901 (E H Pearce's book on CH, 1901).
There are no signs of hats, but this probably does not mean much.
In Clifford Jones book, "Christ´s Hospital Heritage - Postcards", which was on sale on OBD, he has a postcard of the London infirmary.
The cast iron beds are the same as we had in Horsham, but the boys are lying on the beds reading, in full Housey, but covered by a blanket, so it is impossible to see the length of the coats. At least their bands are straight.


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New price and stunning views for this executive detached home within the idyllic and prestigious Bladon Houses!
An attractive traditional detached home set within a prestigious private development on the outskirts of Newton Solney, benefitting from spacious accommodation, three double bedrooms and superb outside space including ample garaging, parking and a mature garden plot. Enjoying an idyllic and peaceful position with countryside views to the rear, this individual detached home has been well maintained throughout its time with the current vendors and offers ideal scope to extend or convert the loft if required.
5 The Close, Bladon Houses, Newton Solney - Guide Price £485,000
The interiors comprise briefly entrance porch, reception hall, lounge, open plan dining kitchen, conservatory, utility, boot room and cloakroom to the ground floor, with three double bedrooms to the first floor serviced by a family bathroom. Outside, the established gardens are laid to generous lawns and a separate kitchen garden, all backing on to open fields to the rear aspect. To the front are further ornamental gardens and there is ample parking, garaging and storage to a workshop, store and purpose built garage. The property is serviced by mains gas central heating and full double glazing.
Situated on the outskirts of Newton Solney, the property benefits from a secluded position within Bladon Houses, a private development home to a handful of similar traditional properties nestled within picturesque Staffordshire countryside. Newton Solney, a highly desirable village, is a charming village home to amenities including two traditional pubs and a village hall. The Newton Solney Church of England Infants feeds into Repton Primary School and John Port Secondary, or alternatively there are also excellent independent schools in the area including St Wystans, Formarke Hall Prep and Repton School. The village is ideally placed for access to the A38 and A50, the closest rail station in Burton providing direct links to Derby, Birmingham and London and the location provides convenient access in around 40 minutes to the International airports of Birmingham and East Midlands.
Traditional Detached Family Home
Well Presented & Spacious Accommodation
Idyllic Position on Private Development
Open Plan Dining Kitchen
Conservatory with Garden Views
Dual Aspect Lounge
Boot Room, Utility & Cloakroom
Three Excellent Double Bedrooms
Sanitan Shower Room
Ample Garaging & Parking
Stunning Mature Grounds
Kitchen Garden with Greenhouse
Scope for Extension/Loft Conversion
Stunning Countryside Views to the Rear
Your 'dream home'... complete with guest house, swimming pool and a tennis court!
SALE AGREED on this stunning character home in the idyllic village of Abbots Bromley
From 'For Sale' to 'SOLD' in under FOUR WEEKS!
**NEW INSTRUCTION** A beautifully presented detached bungalow offering spacious rooms on the rural outskirts of Barton under Needwood
Our first sale of 2020 has been agreed today!
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Barton-under-Needwood
The Promenade,
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Barton-under-Needwood,
DE13 8DZ
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Pryor's competitive nature makes him student of game
CHICAGO -- Let's see what you're made of, rookie, Malcolm Jenkins thought the other day.
Ohio State players were holding an informal seven-on-seven passing drill, and Jenkins, a senior cornerback and world-class trash talker, decided to challenge hotshot freshman quarterback Terrelle Pryor.
"I asked him if he was going to throw me a pick," Jenkins said, breaking into a grin. "And he threw the ball at me every single time. He's not somebody who's going to back down."
Jenkins was only the latest person to experience Pryor's competitiveness, to learn the most important reason why he might make an immediate impact on the Ohio State program in 2008.
The physical abilities are obvious. Pryor is the first player in Pennsylvania high school history to both throw and run for more than 4,000 career yards. He possesses a rare blend of size, speed and strength.
It's why a kid who has yet to play a college game was a hot topic of discussion at the Big Ten preseason meetings this past week.
But when it comes to Pryor, it's not measurables that matter most. It's his attitude. A player who comes to college so highly touted could pose a severe challenge to team chemistry if he gives off a sense of arrogance or entitlement.
"Everybody is telling him how good he is and how he can come in and start and all this other stuff," Jenkins said. "He can be fooled by the media or the recruiting process."
According to those around him, though, one of Pryor's best traits is that he knows how much he doesn't know. He is driven by a desire to improve, and he yearns to be challenged.
Pryor's quarterbacks coach at Jeannette (Pa.) High School, Roy Hall, tells a story of a drill Pryor and his teammates conducted a year ago. The quarterbacks were trying to lob a ball into a 55-gallon drum from 20 yards to help them perfect their touch on lob passes.
"It was time to go into a meeting," Hall said, "and one of the other guys lucks out and gets it in. (Pryor) was late getting to that meeting, because he had to stay out there until he got one in. That's just him."
Hall said he often quoted a particular saying to Pryor as a reminder: "No talent beats talent when talent doesn't work."
Weightlifting sessions in Hall's garage were intense. Already, in Pryor's six weeks in Columbus, Ohio State strength and conditioning coach Eric Lichter has taken note.
"He just seems to be one of those guys who enjoys physical work," Lichter said.
And then Lichter mentioned something that seems minor, but it illustrates that this kid is different.
"Whenever I talk to him, he looks you in the eye the entire time," Lichter said. "He's not distracted by text messaging and his cell phone. He keeps eye contact and he listens to everything you say. Not everybody does that."
Coach Jim Tressel learned a lot about Pryor's eagerness to learn and grow throughout the recruiting process.
After Tressel flew to a Jeannette game last fall and witnessed another Pryor tour de force, he said Pryor was more concerned with a play he missed than with those he made.
"He wanted to explain to me about that one pass he didn't hit: 'I saw the safety and I let it go just a little bit, I should've hit it,' " Tressel said. "He just loves to talk about becoming as good as he can become."
Even Pryor's choice of colleges revealed character. Many schools doubtless tantalized him with promises of immediate playing time.
Tressel, though, made it clear that returning senior Todd Boeckman was the starter. Any playing time Pryor gets will be earned.
"Everyone is like, 'Why not go to Michigan, he's going to run this offense; why not go to Oregon, he's going to run this offense,' " OSU receiver Brian Hartline said. "But it's not about that, it's about the future. So it's a great call for him (to come to OSU). Sit behind a veteran quarterback and learn some things. That speaks a lot about him."
Of course, the possibility exists that Pryor is so good that he will push Boeckman for the starting job this season. Boeckman said he welcomes the competition.
Jenkins, meanwhile, will keep prodding the rookie, testing him. As a team leader, it's his job.
"He can contribute," Jenkins said. "As long as you have the right attitude, it will all work out."
kgordon@dispatch.com