the imaging was performed using a 1300 nm sd - oct system shown in fig .
s1 . a superluminescent diode ( sld ) with a bandwidth of 105 nm was used as the light source , giving an axial resolution of 9 m .
an identical pair of achromatic doublets with focal lengths of 30 mm was used to image the fiber core to the sample , resulting in a numerical aperture ( na ) of 0.1 .
the rayleigh range was calculated to be 50 m ( using 4.7 m as the radius of the beam at the beam waist ) while the imaging depth from the spectrometer ( bayspec , inc . )
the beam was raster scanned along the fast - scanning and slow - scanning axes over the sample .
customized driving waveforms ( 85% linear , 15% fly - back ) for the x - y galvanometer pair ( scanlab , scancube 7 ) were generated by a daq board ( national instruments , ni - pcie-6353 ) , which also generated a control signal to synchronize the scanning with the acquisition from the ingaas line - scan camera ( goodrich , su - ldh2 ) .
the camera was operated at the maximum a - scan rate of 91.912 khz and was interfaced through an image acquisition board ( national instruments , ni - pcie-1427 ) .
the software for data acquisition and graphical user interface was developed in labview and the data was processed in real - time through dynamic link library ( dll ) function calls implemented in c ( microsoft visual studio 2008 environment ) .
a computer with an intel core i7 processor ( 975 @ 3.3 ghz , 12 gb ddr3 ram ) was used for running the system and the compute unified device architecture ( cuda ) extension v4.1 from nvidia was used for gpu kernel calls on the nvidia geforce gtx 580 gpu .
the ex vivo samples were placed on a three - axis stage separate from the beam collimator and scanning galvos while the in vivo data was taken by gently pressing the tissue of interest onto a custom mount attached to the scancube and beam collimator . by attaching a coverslip mount directly to the lens tube containing the objective lens , which was attached to the scanning optics and fiber collimator , the phase stability requirements for isam
acquired volumes consisted of 1024 pixels per a - scan and 810 a - scans along each transverse dimension resulting in an acquisition time of approximately 8.5 seconds .
a multi - streamed gpu program was developed for real - time 3-d isam ( see supplementary fig .
the streams executed concurrently , performing two orthogonal 2-d isam reconstructions where one stream processed the fast - axis frames while the other stream processed the orthogonal dimension of the previously acquired , 2-d isam processed data .
this decomposition required only a single volume buffer in gpu memory at any given time because each previously acquired slow - axis frame can be replaced by the currently acquired fast - axis frame .
all the processing on the gpu was done with single precision floating point operations and gamma correction was applied on the processed data for display purposes . in this manuscript , the term  real - time  means that data acquisition was never paused for processing , and that data is continuously being updated for the user , albeit , the data being displayed is at a small latency of one volume .
( 8.5 seconds for the dimensions mentioned in experimental setup ) . if we were to allow the camera to pause between volume acquisitions to complete the isam reconstruction , the latency would be reduced even further ( to 1.5 seconds for the same volume ) .
see supplementary methods for further details . to remove any bias in displaying comparisons between oct and isam
, all comparisons were viewed on the same histogram scale using the same upper and lower saturation values . in real time , our system has the ability to both process and display cross - sectional and user - selected en face planes in the 2-d and 3-d isam reconstructions . in post - processing for further visualization ,
the calculated energy in each isam tomogram ( en face plane by en face plane ) was normalized to that of the oct tomogram .
after power - normalization , the noise floors in the oct and the isam tomograms were in excellent agreement . to further visualize complete oct and isam datasets ,
the volume was first segmented into two regions , the stratum corneum / stratum lucidum ( containing the sweat - ducts ) and the dermis , then different color maps were used for each .
image metrics such as anisotropy , signal - to - noise ratio , and contrast were computed to quantitatively evaluate the improvement in reconstruction quality .
the anisotropy image quality metric was originally devised to be sensitive to additive gaussian noise in incoherent imaging systems .
further testing on various tissue phantoms and tissue data ( data not shown ) confirmed that this metric is reliable for noise present in oct data as well .
signal - to - noise and contrast were computed by using the 20% ( noise ) and 90% ( signal ) quantiles of the intensity histograms .
the imaging was performed using a 1300 nm sd - oct system shown in fig .
s1 . a superluminescent diode ( sld ) with a bandwidth of 105 nm was used as the light source , giving an axial resolution of 9 m .
an identical pair of achromatic doublets with focal lengths of 30 mm was used to image the fiber core to the sample , resulting in a numerical aperture ( na ) of 0.1 .
the rayleigh range was calculated to be 50 m ( using 4.7 m as the radius of the beam at the beam waist ) while the imaging depth from the spectrometer ( bayspec , inc . )
the beam was raster scanned along the fast - scanning and slow - scanning axes over the sample .
customized driving waveforms ( 85% linear , 15% fly - back ) for the x - y galvanometer pair ( scanlab , scancube 7 ) were generated by a daq board ( national instruments , ni - pcie-6353 ) , which also generated a control signal to synchronize the scanning with the acquisition from the ingaas line - scan camera ( goodrich , su - ldh2 ) .
the camera was operated at the maximum a - scan rate of 91.912 khz and was interfaced through an image acquisition board ( national instruments , ni - pcie-1427 ) .
the software for data acquisition and graphical user interface was developed in labview and the data was processed in real - time through dynamic link library ( dll ) function calls implemented in c ( microsoft visual studio 2008 environment ) .
a computer with an intel core i7 processor ( 975 @ 3.3 ghz , 12 gb ddr3 ram ) was used for running the system and the compute unified device architecture ( cuda ) extension v4.1 from nvidia was used for gpu kernel calls on the nvidia geforce gtx 580 gpu .
the ex vivo samples were placed on a three - axis stage separate from the beam collimator and scanning galvos while the in vivo data was taken by gently pressing the tissue of interest onto a custom mount attached to the scancube and beam collimator . by attaching a coverslip mount directly to the lens tube containing the objective lens , which was attached to the scanning optics and fiber collimator , the phase stability requirements for isam
acquired volumes consisted of 1024 pixels per a - scan and 810 a - scans along each transverse dimension resulting in an acquisition time of approximately 8.5 seconds .
a multi - streamed gpu program was developed for real - time 3-d isam ( see supplementary fig .
the streams executed concurrently , performing two orthogonal 2-d isam reconstructions where one stream processed the fast - axis frames while the other stream processed the orthogonal dimension of the previously acquired , 2-d isam processed data .
this decomposition required only a single volume buffer in gpu memory at any given time because each previously acquired slow - axis frame can be replaced by the currently acquired fast - axis frame .
all the processing on the gpu was done with single precision floating point operations and gamma correction was applied on the processed data for display purposes . in this manuscript , the term  real - time  means that data acquisition was never paused for processing , and that data is continuously being updated for the user , albeit , the data being displayed is at a small latency of one volume .
( 8.5 seconds for the dimensions mentioned in experimental setup ) . if we were to allow the camera to pause between volume acquisitions to complete the isam reconstruction , the latency would be reduced even further ( to 1.5 seconds for the same volume ) .
to remove any bias in displaying comparisons between oct and isam , all comparisons were viewed on the same histogram scale using the same upper and lower saturation values . in real time , our system has the ability to both process and display cross - sectional and user - selected en face planes in the 2-d and 3-d isam reconstructions . in post - processing for further visualization ,
the calculated energy in each isam tomogram ( en face plane by en face plane ) was normalized to that of the oct tomogram .
after power - normalization , the noise floors in the oct and the isam tomograms were in excellent agreement . to further visualize complete oct and isam datasets , the tomograms were depth - normalized to a common histogram scale .
the volume was first segmented into two regions , the stratum corneum / stratum lucidum ( containing the sweat - ducts ) and the dermis , then different color maps were used for each .
image metrics such as anisotropy , signal - to - noise ratio , and contrast were computed to quantitatively evaluate the improvement in reconstruction quality .
the anisotropy image quality metric was originally devised to be sensitive to additive gaussian noise in incoherent imaging systems .
further testing on various tissue phantoms and tissue data ( data not shown ) confirmed that this metric is reliable for noise present in oct data as well .
signal - to - noise and contrast were computed by using the 20% ( noise ) and 90% ( signal ) quantiles of the intensity histograms .
 high - resolution real - time tomography of scattering tissues is important for many areas of medicine and biology16 . 
 however , the compromise between transverse resolution and depth - of - field in addition to low sensitivity deep in tissue continue to impede progress towards cellular - level volumetric tomography . 
 computed imaging has the potential to solve these long - standing limitations . 
 interferometric synthetic aperture microscopy ( isam)79 is a computed imaging technique enabling high - resolution volumetric tomography with spatially invariant resolution . however , its potential for clinical diagnostics remains largely untapped since full volume reconstructions required lengthy postprocessing , and the phase - stability requirements have been difficult to satisfy in vivo . 
 here we demonstrate how 3-d fourier - domain resampling , in combination with high - speed optical coherence tomography ( oct ) , can achieve high - resolution in vivo tomography . 
 enhanced depth sensitivity was achieved over a depth - of - field extended in real time by more than an order of magnitude . 
 this work lays the foundation for high - speed volumetric cellular - level tomography . 
Methods
Experimental setup
GPU implementation
Image display and analysis
Supplementary Material