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Deep Learning Based Topology Guaranteed Surface And Mme Segmentation Of Multiple Sclerosis Subjects From Retinal Oct, Yufan He, Aaron Carass, Yihao Liu, Bruno Jedynak, Sharon D. Solomon, Shiv Saidha, Peter A. Calabresi, Jerry L. Prince
Deep Learning Based Topology Guaranteed Surface And Mme Segmentation Of Multiple Sclerosis Subjects From Retinal Oct, Yufan He, Aaron Carass, Yihao Liu, Bruno Jedynak, Sharon D. Solomon, Shiv Saidha, Peter A. Calabresi, Jerry L. Prince
Mathematics and Statistics Faculty Publications and Presentations
Optical coherence tomography (OCT) is a noninvasive imaging modality that can be used to obtain depth images of the retina. Patients with multiple sclerosis (MS) have thinning retinal nerve fiber and ganglion cell layers, and approximately 5% of MS patients will develop microcystic macular edema (MME) within the retina. Segmentation of both the retinal layers and MME can provide important information to help monitor MS progression. Graph-based segmentation with machine learning preprocessing is the leading method for retinal layer segmentation, providing accurate surface delineations with the correct topological ordering. However, graph methods are time-consuming and they do not optimally incorporate …