Atlas-based shape analysis and classification of retinal optical coherence tomography images using the functional shape (fshape) framework.

We propose a novel approach for quantitative shape variability analysis in retinal optical coherence tomography images using the functional shape (fshape) framework. The fshape framework uses surface geometry together with functional measures, such as retinal layer thickness defined on the layer surface, for registration across anatomical shapes. This is used to generate a population mean template of the geometry-function measures from each individual. Shape variability across multiple retinas can be measured by the geometrical deformation and functional residual between the template and each of the observations. To demonstrate the clinical relevance and application of the framework, we generated atlases of the inner layer surface and layer thickness of the Retinal Nerve Fiber Layer (RNFL) of glaucomatous and normal subjects, visualizing detailed spatial pattern of RNFL loss in glaucoma. Additionally, a regularized linear discriminant analysis classifier was used to automatically classify glaucoma, glaucoma-suspect, and control cases based on RNFL fshape metrics.

Exact surface registration of retinal surfaces from 3-D optical coherence tomography images.

Nonrigid registration of optical coherence tomography (OCT) images is an important problem in studying eye diseases, evaluating the effect of pharmaceuticals in treating vision loss, and performing group-wise cross-sectional analysis. High dimensional nonrigid registration algorithms required for cross-sectional and longitudinal analysis are still being developed for accurate registration of OCT image volumes, with the speckle noise in images presenting a challenge for registration. Development of algorithms for segmentation of OCT images to generate surface models of retinal layers has advanced considerably and several algorithms are now available that can segment retinal OCT images into constituent retinal surfaces. Important morphometric measurements can be extracted if accurate surface registration algorithm for registering retinal surfaces onto corresponding template surfaces were available. In this paper, we present a novel method to perform multiple and simultaneous retinal surface registration, targeted to registering surfaces extracted from ocular volumetric OCT images. This enables a point-to-point correspondence (homology) between template and subject surfaces, allowing for a direct, vertex-wise comparison of morphometric measurements across subject groups. We demonstrate that this approach can be used to localize and analyze regional changes in choroidal and nerve fiber layer thickness among healthy and glaucomatous subjects, allowing for cross-sectional population wise analysis. We also demonstrate the method's ability to track longitudinal changes in optic nerve head morphometry, allowing for within-individual tracking of morphometric changes. This method can also, in the future, be used as a precursor to 3-D OCT image registration to better initialize nonrigid image registration algorithms closer to the desired solution.

Rapid radial optical coherence tomography image acquisition.

We demonstrate how compressive sampling can be used to expedite volumetric optical coherence tomography (OCT) image acquisition. We propose a novel method to interpolate OCT volumetric images from data acquired by radial B-scans in the Cartesian coordinate system. Due to the inherent polar symmetry in the human eye, the (r, θ, z) coordinate system provides a natural domain to perform the interpolation. We demonstrate that the method has minimal effect on image quality even when up to 88% of the data is not acquired. The potential outcome of this work could lead to significant reductions in OCT volume acquisition time in clinical practice.

Quantitative evaluation of transform domains for compressive sampling-based recovery of sparsely sampled volumetric OCT images.

Recently, compressive sampling has received significant attention as an emerging technique for rapid volumetric imaging. We have previously investigated volumetric optical coherence tomography (OCT) image acquisition using compressive sampling techniques and showed that it was possible to recover image volumes from a subset of sampled images. Our previous findings used the multidimensional wavelet transform as the domain of sparsification for recovering OCT image volumes. In this report, we analyzed and compared the potential and efficiency of three other image transforms to reconstruct the same volumetric OCT image. Two quantitative measures, the mean square error and the structural similarity index, were applied to compare the quality of the reconstructed volumetric images. We observed that fast Fourier transformation and wavelet both are capable of reconstructing OCT image volumes for the orthogonal sparse sampling masks used in this report, but with different merits.

Novel surface-smoothing based local gyrification index.

The quantication of cortical surface folding is important in identifying and classifying many neurodegenerative diseases. Much work has been done to identify regional and global brain folding, and in this paper we review some of these methods, as well as propose a new method that has advantages over the existing state of art. Using our novel proposed method, we mapped the local gyrification index on the cortical surface for subjects with mild Alzheimer's dementia (n=20) , very mild dementia (n=23) and age-matched healthy subjects (n=52). In our experiments we find a consistent pattern of gyrification changes in the dementia subjects, with regions generally affected early on in the progression of Alzheimer pathology, including medial temporal lobe, and cingulate gyrus, having decreased gyrification. At the same time we observe increased gyrification in dementia subjects, in frontal, anterior temporal and posteriorly located regions. We speculate that in neurodegenerative diseases including Alzheimer Disease, the folding of the entire cortical mantle undergoes dynamic changes as regional atrophy begins and expands, with both decreases and increases in gyrification.

Real-time high-speed volumetric imaging using compressive sampling optical coherence tomography.

Volumetric imaging of the Optic Nerve Head (ONH) morphometry with Optical Coherence Tomography (OCT) requires dense sampling and relatively long acquisition times. Compressive Sampling (CS) is an emerging technique to reduce volume acquisition time with minimal image degradation by sparsely sampling the object and reconstructing the missing data in software. In this report, we demonstrated real-time CS-OCT for volumetric imaging of the ONH using a 1060nm Swept-Source OCT prototype. We also showed that registration and averaging of CS-recovered volumes enhanced visualization of deep structures of the sclera and lamina cribrosa. This work validates CS-OCT as a means for reducing volume acquisition time and for preserving high-resolution in volume-averaged images. Compressive sampling can be integrated into new and existing OCT systems without changes to the optics, requiring only software changes and post-processing of acquired data.

Rapid volumetric OCT image acquisition using compressive sampling.

Acquiring three dimensional image volumes with techniques such as Optical Coherence Tomography (OCT) relies on reconstructing the tissue layers based on reflection of light from tissue interfaces. One B-mode scan in an image is acquired by scanning and concatenating several A-mode scans, and several contiguous slices are acquired to assemble a full 3D image volume. In this work, we demonstrate how Compressive Sampling (CS) can be used to accurately reconstruct 3D OCT images with minimal quality degradation from a subset of the original image. The full 3D image is reconstructed from sparsely sampled data by exploiting the sparsity of the image in a carefully chosen transform domain. We use several sub-sampling schemes, recover the full 3D image using CS, and show that there is negligible effect on clinically relevant morphometric measurements of the optic nerve head in the recovered image. The potential outcome of this work is a significant reduction in OCT image acquisition time, with possible extensions to speeding up acquisition in other imaging modalities such as ultrasound and MRI.