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2019 | OriginalPaper | Chapter

Min-Cut Segmentation of Retinal OCT Images

Authors : Bashir Isa Dodo, Yongmin Li, Khalid Eltayef, Xiaohui Liu

Published in: Biomedical Engineering Systems and Technologies

Publisher: Springer International Publishing

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Abstract

Optical Coherence Tomography (OCT) is one of the most vital tools for diagnosing and tracking progress of medication of various retinal disorders. Many methods have been proposed to aid with the analysis of retinal images due to the intricacy of retinal structures, the tediousness of manual segmentation and variation from different specialists. However image artifacts, in addition to inhomogeneity in pathological structures, remain a challenge, with negative influence on the performance of segmentation algorithms. In this paper we present an automatic retinal layer segmentation method, which comprises of fuzzy histogram hyperbolization and graph cut methods. We impose hard constraints to limit search region to sequentially segment 8 boundaries and 7 layers of the retina on 150 OCT B-Sans images, 50 each from the temporal, nasal and center of foveal regions. Our method shows positive results, with additional tolerance and adaptability to contour variance and pathological inconsistence of the retinal structures in all regions.

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Title: Min-Cut Segmentation of Retinal OCT Images
Authors: Bashir Isa Dodo
Yongmin Li
Khalid Eltayef
Xiaohui Liu
Publisher: Springer International Publishing
Book: Biomedical Engineering Systems and Technologies
Print ISBN: 978-3-030-29195-2

Electronic ISBN: 978-3-030-29196-9

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-29196-9_5

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