Optical Computational Imaging

The decoupling of axial and transverse resolution makes OCT possible to achieve rapid volumetric imaging with millimeter-scale imaging depth and micrometer-scale axial resolution by using a low numerical aperture (NA) optical system. The use of low-NA optics, however, comes at the expense of low transverse resolution. In many medical and surgical scenarios, however, higher transverse resolution for visualizing cellular features in vivo is desirable. Therefore, the long-standing trade-off between transverse resolution and depth-of-field (DOF) limits further development of OCT. As a broadband interferometry-based imaging technique, dispersion mismatch between the sample and reference paths negatively affects the axial resolution in OCT. Fully compensating for dispersion leads to the highest image quality, but this is often difficult to achieve in practice. Likewise, in some cases it is not desirable, or perhaps not possible, to achieve high-quality aberration-free imaging optics. In this case, aberrations can severely degrade the OCT image quality. Together, these limitations of dispersion mismatch, DOF, and optical aberration lead to restricted performance of an otherwise powerful imaging technology. One aim of the Biophotonics Imaging Laboratory is to develop noval optical computational imaging techniques to overcome these limitations.

Interferometric Synthetic Aperture Microscopy (ISAM)

State-of-the-art methods in high-resolution three-dimensional optical microscopy require that the focus be scanned through the entire region of interest. However, an analysis of the physics of the light-sample interaction reveals that the Fourier space coverage is independent of depth. We have shown that by solving the inverse scattering problem for coherence microscopy, computed reconstruction yields volumes with a resolution in all planes that is equivalent to the resolution achieved only at the focal plane for conventional high-resolution microscopy. The entire illuminated volume has spatially-invariant resolution, thus eliminating the compromise between resolution and depth-of-field. This novel computational image-formation technique is capable of real-time imaging, and has the potential to broadly impact real-time 3-D microscopy and analysis in the fields of cell and tumor biology, as well as in clinical diagnosis where in vivo imaging is preferable to biopsy. We have analyzed and demonstrated this technique for rectangular Cartesian-coordinate imaging, for rotational catheter-based imaging, and for full-field imaging.

 

Renderings of 3-D OCT (left) and 3-D ISAM reconstruction (right) of a silicone tissue phantom containing 1 m TiO2 scatterers, demonstrating spatially invariant resolution.

 

En face images from human breast tissue. Images are shown for different depths. Histological sections (a,b) show comparable features with respect to the unprocessed interferometric data (c,d) and the ISAM reconstructions (e,f). The ISAM reconstructions resolve features in the tissue that are not decipherable from the unprocessed data. The green dashed arrow indicates the fast-scanning direction for the volumetric data acquisition.

Ralston TS, Marks DL, Carney PS, Boppart SA. Interferometric synthetic aperture microscopy.  Nature Physics, 3:129-134, 2007. n/a PDF

 

 

En face ISAM and OCT images from rat adipose tissue ex vivo showing that ISAM reconstruction of a plane far from focus provides comparable resolution to moving the focus to that plane. (a) En face OCT of a plane approximately 8 Rayleigh ranges above focus. (b) ISAM reconstruction of the same en face plane. (c) En face OCT with the focal plane moved to the plane of interest in (a). The field of view in each panel is 500 m by 500 m.

Ralston TS, Adie SG, Marks DL, Boppart SA, Carney PS. Cross-validation of interferometric synthetic aperture microscopy and optical coherence tomography.  Optics Letters, 35:1683-1685, 2010. n/a n/a

 

 

​​

Real-time ISAM visualization of highly-scattering in vivo human skin from the wrist region acquired using a 0.1 NA OCT system, after placing the focus 1.2 mm beneath the skin surface. Cross-sectional results of (a) OCT and (b) ISAM. En face planes of (c) OCT and (d) ISAM at an optical depth of 520 µm into the tissue. (e) Variation of SNR with depth shows the improvement of ISAM, which was computed using the 20% (noise) and 90% (signal) quantiles of the intensity histograms. Compared to OCT, ISAM shows significant improvement over an extended depth range. CS, coverslip; GL, glycerol; SD, stratum disjunction; SC, stratum corneum; RD, reticular dermis; SF, subcutaneous fat. Scale bars represent 500 µm.

Ahmad A,  Shemonski ND, Adie  SG,  Kim HS,  Hwu WMW,  Carney PS, and  Boppart SA, "Real-time in vivo computed optical interferometric tomography," Nat. Photonics 7: 444–448, 2013.

PubMed Abstract

PDF

 

 

​​

Ex vivo human breast tissue acquired from a NA 0.6 OCM system. 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.

Liu YZ, Shemonski ND, Adie SG, Ahmad A, Bower AJ, Carney PS, and Boppart SA, "Computed optical interferometric tomography for high-speed volumetric cellular imaging," Biomed. Opt. Express 5(9), 2988–3000, 2014

PubMed Abstract

PDF

 

 

Simulated (left) and reconstructed (right) radial OCT catheter images of randomly distributed point scatterers.

Marks DL, Ralston TS, Carney PS, Boppart SA.  Inverse scattering for rotationally scanned optical coherence tomography.  J. Opt. Soc. Am. A, 23(10):2433-2439, 2006.

PubMed Abstract

PDF

 

Computational Adaptive Optics (CAO)

Aberration, which causes a deviation of an ideal wavefront, is an important issue affecting image quality in many imaging modalities. With increased NA for higher transverse resolution, the optical wavefront is more susceptible to being distorted by the imperfections of the imaging optics and the sample itself. As a result, the resolution may decrease, as well as the contrast and the signal-to-noise ratio. OCT/OCM also share this limitation are directly affected by aberrations in the system optics or the sample. Sophisticated optical designs can suppress the static system aberrations, but they are not versatile for complex biological tissues that introduce unique, often dynamically changing, sample aberrations. Hardware-based adaptive optics (HAO) physically sense and correct the aberrations for improving the signal strength and resolution. The systems, however, remain expensive and complex. In addition, the aberration compensation can only be valid for one isoplanatic patch during the imaging procedure, which extends the time of the imaging session for the application of large volumetric imaging. We have utilized the phase information of OCT/OCM to compensate the aberrations through post-processing.

Complex signals from the silicone phantom data, showing the impact of computational correction of astigmatism on both the amplitude and phase. Images are arranged in columns according to the type of processing applied. The en face (x-y) planes shown are from the 3D silicone phantom dataset near (A) the upper line focus (z = 300 μm), (B) the plane of least confusion (z = 0 μm), and (C) the lower line foci (z = -300 μm), where the units of the z axis denote optical path length. Dimensions of all images are 256 × 256 μm.

Adie SG, Graf BW, Ahmad A, Carney PS, and Boppart SA, "Computational adaptive optics for broadband optical interferometric tomography of biological tissue," Proc. Natl. Acad. Sci. U. S. A. 109(19), 7175–7180, 2012

PubMed Abstract

PDF

 

 

 

Volumetric cellular-resolution imaging of in vivo human skin acquired using a 0.6 NA point-scanning SD-OCM system without depth scanning. (a-e) En face results at different depths based-on the standard OCT processing. (f-j) ISAM and CAO processing for (a-e), respectively. Arrows indicate (f) boundary of the stratum corneum and epidermis, (g) granular cell nuclei, (h) dermal papillae, (i) basal cells, and (j) connective tissue. Scale bar represents 40 µm.

Liu YZ, Shemonski ND, Adie SG, Ahmad A, Bower AJ, Carney PS, and Boppart SA, "Computed optical interferometric tomography for high-speed volumetric cellular imaging," Biomed. Opt. Express 5(9), 2988–3000, 2014

PubMed Abstract

PDF

 

 

 

Fovea images of the living human retina. (a) A fundus image showing the location of the acquired en face OCT data. (b) Original en face OCT data. (c) En face OCT data after CAO. N, nasal; S, superior. Scale bars represent 2 degrees in (a) and 0.5 degrees in (b, c).

Shemonski ND, South SA, Liu YZ, Adie SG, Carney PS, and Boppart SA, "Computational high-resolution optical imaging of the living human retina," Nat. Photonics 9(7), 440–443, 2015

PubMed Abstract

PDF

 

Dispersion Compensation Algorithms

Practical clinical optical coherence tomography systems require automatic tools for identifying and correcting flaws in OCT images. One type of flaw is the loss of image detail owing to the dispersion of the medium, which in most cases is unknown. We have developed an autofocus algorithm for estimating the delay line and material dispersion from OCT reflectance data. This autofocus algorithm can be used in conjunction with a high-speed, digital-signal-processor-based OCT acquisition system for rapid image correction.

 

On the left is a cross section schematic of a PDMS microfluidic structure. On the right are autofocus digitally corrected reflections off of interfaces of the microfluidic structure. Plots (a), (c), (e), and (g) correspond to the uncorrected reflectance functions, whereas (b), (d), (f), and (h) are the corrected point spread functions.

Marks Dl, Oldenburg AL, Reynolds JJ, Boppart SA. Digital algorithm for dispersion correction in optical coherence tomography for homogeneous and stratified media. Appl. Opt. 42:204-217, 2003. PubMed
Abstract
PDF
Marks DL, Oldenburg AL, Reynolds JJ, Boppart SA. Autofocus algorithm for dispersion correction in optical coherence tomography. Applied Optics 42:3038-3046, 2003. PubMed
Abstract
PDF

 

Adaptive Spectal Adopization

In optical coherence tomography (OCT), as in other imaging modalities, one desires to achieve the highest possible resolution given instrument limitations. The bandwidth of the OCT source chiefly determines the useful resolution. However, if the spectrum is not smooth, then the point response in the interferogram will have large sidelobes that cause a degradation of effective resolution and introduce artifacts. As a result, a smooth, Gaussian-like spectrum is often employed to minimize sidelobes. However, there are many sources that do not produce smooth spectra but still produce a wide bandwidth, such as Ti-sapphire oscillators, nonlinear supercontinuum generation optical fibers including microstructured and tapered fibers, and ultrahigh-numerical-aperture fiber sources. We have created a method that produces an estimate of object scattering density (or reflectivity profile) that minimizes sidelobes while not overly increasing the contribution of noise. This method can make broad spectrum sources much more useful for high-resolution OCT.

 

Spectrum of source (solid line) and sidelobe-corrected instrument response function (dashed line). The OCT system used a UHNA3 fiber as a source, and spectra were obtained from the reflections off of a microscope slide.

Point response of original spectrum (top) and sidelobe-corrected instrument response function (bottom) obtained with a microscope slide as a test sample.

Marks DL, Carney PS, Boppart SA. Adaptive spectral apodization for side-lobe reduction in optical coherence tomography. J. Biomed. Optics, 9:1281-1287, 2004. PubMed Abstract PDF

 

Projected Index Computed Tomography (PICT)

Projected index computed tomography (PICT) is an imaging technique that provides a computed reconstruction of the index of refraction of a sample. PICT makes use of data from standard optical coherence tomography images taken from several view angles to determine a mapping of the refractive indices of the sample. A rectilinear propagation model is assumed, so the data are understood to be related to the line integral of the refractive index in the beam paths. These data thus provide a set of angular projections of the sample. The spatial distribution of the index of the object may then be reconstructed by use of standard filtered backprojection techniques. The resultant PICT images are free of the spatial distortion that is inherent in standard optical cross-sectional images and correspond well to the manufactured dimensions of specific samples. PICT has the potential to produce high-resolution, highly sensitive, and spatially accurate images of a variety of biological and material samples.

 

Glass capillary tube sample (left) is imaged by PICT method (right), which shows a spatial map refractive index. Linear artifacts in the image stem from the sharp discontinuities in projected data.

Zysk A, Reynolds JJ, Marks DL, Carney PS, Boppart SA. Projected index computed tomography. Opt. Letters 28:701-703, 2003. PubMed
Abstract
PDF