Intra-retinal segmentation of optical coherence tomography images using active contours with a dynamic programming initialization and an adaptive weighting strategy

Peyman Gholami; Priyanka Roy; Mohana Kuppuswamy Parthasarathy; Abbas Ommani; John Zelek; Vasudevan Lakshminarayanan

doi:10.1117/12.2292095

14 February 2018 Intra-retinal segmentation of optical coherence tomography images using active contours with a dynamic programming initialization and an adaptive weighting strategy

Peyman Gholami, Priyanka Roy, Mohana Kuppuswamy Parthasarathy, Abbas Ommani, John Zelek, Vasudevan Lakshminarayanan

Author Affiliations +

Proceedings Volume 10483, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXII; 104832M (2018) https://doi.org/10.1117/12.2292095
Event: SPIE BiOS, 2018, San Francisco, California, United States

Abstract

Retinal layer shape and thickness are one of the main indicators in the diagnosis of ocular diseases. We present an active contour approach to localize intra-retinal boundaries of eight retinal layers from OCT images. The initial locations of the active contour curves are determined using a Viterbi dynamic programming method. The main energy function is a Chan-Vese active contour model without edges. A boundary term is added to the energy function using an adaptive weighting method to help curves converge to the retinal layer edges more precisely, after evolving of curves towards boundaries, in final iterations. A wavelet-based denoising method is used to remove speckle from OCT images while preserving important details and edges. The performance of the proposed method was tested on a set of healthy and diseased eye SD-OCT images. The experimental results, compared between the proposed method and the manual segmentation, which was determined by an optometrist, indicate that our method has obtained an average of 95.29%, 92.78%, 95.86%, 87.93%, 82.67%, and 90.25% respectively, for accuracy, sensitivity, specificity, precision, Jaccard Index, and Dice Similarity Coefficient over all segmented layers. These results justify the robustness of the proposed method in determining the location of different retinal layers.

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Peyman Gholami, Priyanka Roy, Mohana Kuppuswamy Parthasarathy, Abbas Ommani, John Zelek, and Vasudevan Lakshminarayanan "Intra-retinal segmentation of optical coherence tomography images using active contours with a dynamic programming initialization and an adaptive weighting strategy", Proc. SPIE 10483, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXII, 104832M (14 February 2018); https://doi.org/10.1117/12.2292095

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