Conventional ultrasound scanners create two-dimensional B-mode images of tissue in which the brightness of a pixel is based on the intensity of the echo return. The basic signal processing chain in the conventional B mode is depicted in FIG. 1. An ultrasound transducer array 2 is activated to transmit an acoustic burst along a scan line. The return RF signals are detected by the transducer elements and then formed into a receive beam by the beamformer 4. The beamformer output data (I/Q or RF) for each scan line is passed through a B-mode processing chain 6 which includes an equalization filtering, envelope detection and logarithmic compression. Depending on the scan geometry, up to a few hundred vectors may be used to form a single acoustic image frame. To smooth the temporal transition from one acoustic frame to the next, some acoustic frame averaging 8 may be performed before scan conversion. The frame averaging may be implemented by a FIR or an IIR filter. In general, the compressed images are in R-.theta. format (for a sector scan) which is converted by the scan converter 10 into X-Y format for video display. On some systems, frame averaging may be performed on the video X-Y data (indicated by dashed block 12) rather than the acoustic frames before scan conversion, and sometimes duplicate video frames may be inserted between acoustic frames in order to achieve a given video display frame rate (typically 30 Hz). The video frames are passed on to a video processor 14, which basically maps the video data to a display gray map for video display.
System control is centered in a host computer 20, which accepts operator inputs through an operator interface 22 (e.g., a keyboard) and in turn controls the various subsystems. (In FIG. 1, only the image data transfer paths are depicted.) During B-mode imaging, a long sequence of the most recent images are stored and continuously updated automatically in a cine memory 16. Some systems are designed to save the R-.theta. acoustic images (this data path is indicated by the dashed line in FIG. 1), while other systems store the X-Y video images. The image loop stored in cine memory 16 can be reviewed via track-ball control, and a section of the image loop can be selected for hard disk storage. For an ultrasound scanner with free-hand three-dimensional imaging capability, the selected image sequence stored in cine memory 16 is transferred to the host computer 20 for three-dimensional reconstruction. The result is written back into another portion of the cine memory, from where it is sent to the display system 18 via video processor 14.
Referring to FIG. 2, the scan converter 10 comprises an acoustic line memory 24 and an X-Y memory 26. The B-mode data stored in polar coordinate (R-.theta.) sector format in acoustic line memory 24 is transformed to appropriately scaled Cartesian coordinate intensity data, which is stored in X-Y memory 26. A multiplicity of successive frames of B-mode data are stored in cine memory 16 on a first-in, first-out basis. The cine memory is like a circular image buffer that runs in the background, continually capturing image data that is displayed in real time to the user. When the user freezes the system, the user has the capability to view image data previously captured in cine memory.
The host computer 20 comprises a central processing unit (CPU) 28 and a random access memory 30. The CPU 28 has read only memory incorporated therein for storing routines used in transforming an acquired volume of intensity data into a multiplicity of three-dimensional projection images taken at different angles. The CPU 28 controls the X-Y memory 26 and the cine memory 16 via the system control bus 32. In particular, the CPU 28 controls the flow of data from the acoustic line memory 24 or from the X-Y memory 26 of the scan converter 10 to the video processor 14 and to the cine memory 16, and from the cine memory to the video processor 14 and to the CPU 28 itself. Each frame of imaging data, representing one of a multiplicity of scans or slices through the object being examined, is stored sequentially in the acoustic line memory 24, in the X-Y memory 26 and in the video processor 14. IN parallel, image frames from either the acoustic line memory or the X-Y memory are stored in cine memory 16. A stack of frames, representing the scanned object volume, is stored in section 16A of cine memory 16.
Two-dimensional ultrasound images are often hard to interpret due to the inability of the observer to visualize the two-dimensional representation of the anatomy being scanned. However, if the ultrasound probe is swept over an area of interest and two-dimensional images are accumulated to form a three-dimensional volume, the anatomy becomes much easier to visualize for both the trained and untrained observer.
In order to generate three-dimensional images, the CPU 28 can perform a series of transformations using a ray casting algorithm such as the one disclosed in U.S. Pat. Nos. 5,226,113 or 5,485,842. The ray-casting technique is applied to the data for the source data volume of interest retrieved from section 16A of cine memory 16. The successive transformations may involve a variety of projection techniques such as maximum, minimum, composite, surface or averaged projections made at angular increments, e.g., at 10.degree. intervals, within a range of angles, e.g., +90.degree. to -90.degree.. Each pixel in the projected image includes the transformed data derived by projection onto a given image plane. In addition, at the time when the cine memory was frozen by the operator, the CPU 28 optionally stores the last frame from the X-Y memory 28 at multiple successive addresses in section 16B of cine memory 16. The projected image data for the first projected view angle is written into the first address in cine memory section 16B, so that the projected image data in a region of interest is superimposed on the background frame. This process is repeated for each angular increment until all projected images are stored in cine memory section 16B, each projected image frame consisting of a region of interest containing transformed intensity data and optionally a background perimeter surrounding the region of interest consisting of background intensity data not overwritten by the transformed intensity data. The background image makes it clearer where each displayed projection is being viewed from. The operator can then select any one of the projected images for display. In addition, the sequence of projected images can be replayed on the display monitor to depict the object volume as if it were rotating in front of the viewer.
Various types of multi-row transducer arrays, including so-called "1.25D" and "1.5D" arrays, have been developed to improve upon the limited elevation performance of present single-row ("1") arrays. As used herein, these terms have the following meanings: 1D) elevation aperture is fixed and focus is at a fixed range; 1.25D) elevation aperture is variable, but focusing remains static; and 1.5D) elevation aperture, shading, and focusing are dynamically variable, but symmetric about the centerline of the array.
In free-hand three-dimensional ultrasound scans, a transducer array (1D to 1.5D) is translated in the elevation direction to acquire a substantially parallel set of image planes through the anatomy of interest. These images can be stored in the cine memory and later retrieved by the system computer for three-dimensional reconstruction. If the spacings between image frames are known, then the three-dimensional volume can be reconstructed with the correct aspect ratio between the out-of-plane and scan plane dimensions. If, however, the estimates of the interslice spacing are poor, significant geometric distortion of the three-dimensional object can result.
In the prior art, a variety of motion control and position-sensing methods have been proposed to control or track the elevational motion of the probe respectively. However, these systems are often costly and cumbersome to use in a clinical environment. Therefore, to reconstruct a three-dimensional image with good resolution in the elevation direction, it is highly desirable to be able to estimate the scan plane displacements directly from the degree of speckle decorrelation between successive image frames.
In International Patent WO 97/00482, Fowlkes et al. proposed a scan plane motion tracking method which is based on computing the correlation between image frames. It was stated that their correlation method is an adaptation of the decorrelation techniques used for monitoring blood flow. A review of such prior art indicates that there are two general approaches as follows:
(1) Trahey et al., in "Speckle pattern correlation with lateral aperture translation: experimental results and implications for spatial compounding," IEEE Trans. Ultrasonics, Ferroelec. and Freq. Control, Vol. UFFC-33 (1986), pp. 257-264, reported the first study that used a full correlation function of intensities in ultrasound images. This approach uses RF or detected image data prior to compression, which is evident from the fact that the correlation function is normalized by the total echo intensities (i.e., is system gain dependent). Chen et al., in "Determination of scan-plane motion using speckle decorrelation: theoretical considerations and initial test," Int. J. Imaging Syst. Technol., Vol. 8 (1997), pp. 38-44, reported phantom studies using this correlation method for three-dimensional sweep distance estimation.
(2) Bohs et al., in "A novel method for angle independent ultrasonic imaging of blood flow and tissue motion," IEEE Trans. Biomed. Eng., Vol. 38 (1991), pp. 280-286, proposed a simpler correlation method which should work with compressed ultrasound images. This is referred to as the SAD method since it is based on computing the sum of absolute differences between corresponding pixels in two kernels being correlated. This computationally efficient method was found to perform almost as well as the full correlation function of Trahey et al. Shehada et al., in "Ultrasound methods for investigating the non-Newtonian characteristics of whole blood," IEEE Trans. Ultrasonics, Ferroelec. and Freq. Control, Vol. UFFC-41 (1994), pp. 96-104, also reported a flow measurement study based on SAD correlation of ultrasound images. For flow measurement, the SAD method basically consists of finding the displacement vector within the scan plane that minimizes the SAD, so only relative changes in SAD are pertinent. In general, however, for a given kernel size the SAD can vary significantly with dynamic range setting and post-processing filtering.
On ultrasound scanners with three-dimensional free-hand scan capability, the images stored in cine memory typically have already gone through a logarithmic or some other highly nonlinear compression for display (typically an 8-bit amplitude display). These images may have also gone through some post-processing filters such as for smoothing or edge enhancement. The compression and filtering operations are often not reversible, and any attempt to make even an approximate "decompression" may introduce quantization noise in the images. For this reason, the first approach discussed above, which is designed for pre-compressed images, may not be most suitable for sweep speed estimation.
The SAD approach works with compressed images and has the advantage of computational speed. However, for three-dimensional reconstruction we need to quantify the actual decorrelation from frame to frame in order to estimate the sweep distance. Using SAD alone would require calibration for all possible combinations of display dynamic range (which may be depth dependent), filters, kernel size and kernel depth position.
Thus, there is a need for a new correlation index that adapts to different dynamic range settings and post-processing filters.