@inproceedings {199, title = {Despeckling vs averaging of retinal UHROCT tomograms: advantages and limitations}, booktitle = {Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XV}, year = {2011}, publisher = {SPIE}, organization = {SPIE}, abstract = {

Imaging time can be reduced using despeckled tomograms, which have similar image metrics to those obtained by averaging several low speed tomograms or many high speed tomograms. Quantitative analysis was used to compare the performance of two speckle denoising approaches, algorithmic despeckling and frame averaging, as applied to retinal OCT images. Human retinal tomograms were acquired from healthy subjects with a research grade 1060nm spectral domain UHROCT system with 5μm axial resolution in the retina. Single cross-sectional retinal tomograms were processed with a novel speckle denoising algorithm and compared with frame averaged retinal images acquired at the same location. Image quality metrics such as the image SNR and contrast-to-noise ratio (CNR) were evaluated for both cases.

}, keywords = {biomedical optics, image processing, medical imaging, optical coherence tomography, speckle}, doi = {http://dx.doi.org/10.1117/12.875867}, url = {http://link.aip.org/link/?PSI/7889/78893C/1}, author = {D D. Lee and K Bizheva and A Wong and J A. Eichel and P Fieguth and D A. Clausi}, editor = {J A. Izatt and J G. Fujimoto and V V. Tuchin} } @inproceedings {204, title = {Positioning systems for high resolution tissue imaging}, booktitle = {SPIE: Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XVIII}, year = {2011}, publisher = {SPIE Proceedings}, organization = {SPIE Proceedings}, address = {San Francisco, USA}, abstract = {

Tissue handling systems position ex-vivo samples to a required accuracy that depends on the features to be imaged. For example, to resolve cellular structure, micron pixel spacing is needed. 3D tissue scanning at cellular resolution allows for more complete histology to be obtained and more accurate diagnosis to be made. However, accurate positioning of a light beam on the sample is a significant challenge, especially when fine spacing between scan steps is desired or large, inconsistently shaped samples need to be imaged. Optical coherence tomography (OCT) is an application where accurate positioning systems are required to reap the full benefit of the technology. By simultaneously manipulating the light beam position and sample location, a 3D image is reconstructed from a series of depth profiles produced. To automate image acquisition, a fully integrated and synchronised system is necessary. A tissue handling and light delivery system for free-space optical devices is described. Performance characteristics such as resolution, uncertainty, and repeatability are evaluated for novel hardware configurations of OCT. Typical scanning patterns with associated synchronisation requirements are discussed.

}, keywords = {galvanometer, light delivery, optical coherence tomography, positioning system, synchronisation}, doi = {http://dx.doi.org/10.1117/12.875156}, author = {T M. Haylock and A T. Cenko and L M. Chifman and P B. Christensen and F Kazemzadeh and A R. Hajian and J Hendrikse and J T. Meade} } @article {278, title = {Intra-retinal layer segmentation in optical coherence tomography images}, journal = {Optics Express}, volume = {17}, year = {2009}, pages = {23719{\textendash}23728}, abstract = {

Retinal layer thickness, evaluated as a function of spatial position from optical coherence tomography (OCT) images is an important diagnostics marker for many retinal diseases. However, due to factors such as speckle noise, low image contrast, irregularly shaped morphological features such as retinal detachments, macular holes, and drusen, accurate segmentation of individual retinal layers is difficult. To address this issue, a computer method for retinal layer segmentation from OCT images is presented. An efficient two-step kernel-based optimization scheme is employed to first identify the approximate locations of the individual layers, which are then refined to obtain accurate segmentation results for the individual layers. The performance of the algorithm was tested on a set of retinal images acquired in-vivo from healthy and diseased rodent models with a high speed, high resolution OCT system. Experimental results show that the proposed approach provides accurate segmentation for OCT images affected by speckle noise, even in sub-optimal conditions of low image contrast and presence of irregularly shaped structural features in the OCT images.

}, keywords = {algorithms and filters, image processing, image recognition, optical coherence tomography, Optical diagnostics for medicine}, doi = {http://dx.doi.org/10.1364/OE.17.023719}, url = {http://www.opticsexpress.org/abstract.cfm?URI=oe-17-26-23719}, author = {K Bizheva and A Mishra and A Wong and D A. Clausi} } @inproceedings {289, title = {A novel algorithm for extraction of the layers of the cornea}, booktitle = {6th Canadian Conference on Computer and Robot Vision}, year = {2009}, month = {05/2009}, address = {Kelowna, British Columbia, Canada}, abstract = {

Accurate corneal layer boundary extraction from optical coherence tomograms can provide precise layer thickness measurements required in the analysis of corneal disease. This paper establishes a novel approach to precisely obtain the five primary corneal layer boundaries. The proposed method determines correspondence relationships between the layer boundaries to facilitate robust boundary extraction in the presence of noise and artifacts. The first phase of the method applies morphological operators to enhance the prominent structural features of the cornea. The second phase uses a semi-automated segmentation algorithm to extract the upper and lower boundaries of the cornea; these boundaries are used to register the corneal image. The final phase extracts all five boundaries using a global optimization method exploiting the medial correspondence relationship between each layers. The proposed method is tested and verified using a representative set of optical coherence tomography images and compared against several state of the art methods. The proposed method is demonstrated to be more robust to noise, to provide more accurate segmentation results, and to require fewer user interactions than the other published methods.

}, keywords = {corneal disease, corneal image register, corneal layer boundary extraction, diseases, eye, Feature Extraction, global optimization method, image registration, image segmentation, layer thickness measurements, medical image processing, optical coherence tomography, optical tomography, optimisation, semiautomated segmentation algorithm, thickness measurement}, doi = {http://dx.doi.org/10.1109/CRV.2009.22}, author = {J A. Eichel and A Mishra and D A. Clausi and P Fieguth} }