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Mathematics and Statistics Faculty Publications and Presentations

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Full-Text Articles in Ophthalmology

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 Jan 2019

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 …


Voxel Based Morphometry In Optical Coherence Tomography: Validation & Core Findings, Bhavna J. Antony, Min Chen, Aaron Carass, Bruno M. Jedynak, Omar Al-Louzi, Sharon D. Solomon, Shiv Saidha, Peter Calabresi, Jerry L. Prince Jan 2016

Voxel Based Morphometry In Optical Coherence Tomography: Validation & Core Findings, Bhavna J. Antony, Min Chen, Aaron Carass, Bruno M. Jedynak, Omar Al-Louzi, Sharon D. Solomon, Shiv Saidha, Peter Calabresi, Jerry L. Prince

Mathematics and Statistics Faculty Publications and Presentations

Optical coherence tomography (OCT) of the human retina is now becoming established as an important modality for the detection and tracking of various ocular diseases. Voxel based morphometry (VBM) is a long standing neuroimaging analysis technique that allows for the exploration of the regional differences in the brain. There has been limited work done in developing registration based methods for OCT, which has hampered the advancement of VBM analyses in OCT based population studies. Following on from our recent development of an OCT registration method, we explore the potential benefits of VBM analysis in cohorts of healthy controls (HCs) and …