Automated segmentation of the ciliary muscle in OCT images using fully convolutional networks
Resumen: Quantifying shape changes in the ciliary muscle during accommodation is essential in understanding the potential role of the ciliary muscle in presbyopia. The ciliary muscle can be imaged in-vivo using OCT but quantifying the ciliary muscle shape from these images has been challenging both due to the low contrast of the images at the apex of the ciliary muscle and the tedious work of segmenting the ciliary muscle shape. We present an automatic-segmentation tool for OCT images of the ciliary muscle using fully convolutional networks. A study using a dataset of 1,039 images shows that the trained fully convolutional network can successfully segment ciliary muscle images and quantify ciliary muscle thickness changes during accommodation. The study also shows that EfficientNet outperforms other current backbones of the literature.
Idioma: Inglés
DOI: 10.1364/BOE.455661
Año: 2022
Publicado en: Biomedical Optics Express 13, 5 (2022), 2810-2823
ISSN: 2156-7085

Factor impacto JCR: 3.4 (2022)
Categ. JCR: BIOCHEMICAL RESEARCH METHODS rank: 28 / 77 = 0.364 (2022) - Q2 - T2
Categ. JCR: RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING rank: 43 / 135 = 0.319 (2022) - Q2 - T1
Categ. JCR: OPTICS rank: 36 / 99 = 0.364 (2022) - Q2 - T2

Factor impacto CITESCORE: 6.7 - Biochemistry, Genetics and Molecular Biology (Q2) - Physics and Astronomy (Q1)

Factor impacto SCIMAGO: 0.955 - Biotechnology (Q1) - Atomic and Molecular Physics, and Optics (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2020-113822RB-C12
Financiación: info:eu-repo/grantAgreement/ES/MICIU/PRE2018-084021
Tipo y forma: Article (Published version)
Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)

Rights Reserved All rights reserved by journal editor

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