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Proceedings Paper

Segmenting retinal OCT images with inter-B-scan and longitudinal information
Author(s): Yufan He; Aaron Carass; Yihao Liu; Angeliki Filippatou; Bruno M. Jedynak; Sharon D. Solomon; Shiv Saidha; Peter A. Calabresi; Jerry L. Prince
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Paper Abstract

Monitoring retinal thickness of persons with multiple sclerosis (MS) provides important bio-markers for disease progression. However, changes in retinal thickness can be small and concealed by noise in the acquired data. Consistent longitudinal retinal layer segmentation methods for optical coherence tomography (OCT) images are crucial for identifying the real longitudinal retinal changes of individuals with MS. In this paper, we propose an iterative registration and deep learning based segmentation method for longitudinal 3D OCT scans. Since 3D OCT scans are usually anisotropic with large slice separation, we extract B-scan features using 2D deep networks and utilize inter-B-scan context with convolutional long-short-term memory (LSTM). To incorporate longitudinal information, we perform fundus registration and interpolate the smooth retinal surfaces of the previous visit to use as a prior on the current visit.

Paper Details

Date Published: 10 March 2020
PDF: 6 pages
Proc. SPIE 11313, Medical Imaging 2020: Image Processing, 113133C (10 March 2020); doi: 10.1117/12.2549857
Show Author Affiliations
Yufan He, Johns Hopkins Univ. (United States)
Aaron Carass, Johns Hopkins Univ. (United States)
Yihao Liu, Johns Hopkins Univ. (United States)
Angeliki Filippatou, The Johns Hopkins Univ. School of Medicine (United States)
Bruno M. Jedynak, Portland State Univ. (United States)
Sharon D. Solomon, Wilmer Eye Institute, The Johns Hopkins Univ. School of Medicine (United States)
Shiv Saidha, The Johns Hopkins Univ. School of Medicine (United States)
Peter A. Calabresi, The Johns Hopkins Univ. School of Medicine (United States)
Jerry L. Prince, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 11313:
Medical Imaging 2020: Image Processing
Ivana Išgum; Bennett A. Landman, Editor(s)

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