000117609 001__ 117609
000117609 005__ 20240319080952.0
000117609 0247_ $$2doi$$a10.1364/BOE.455661
000117609 0248_ $$2sideral$$a128815
000117609 037__ $$aART-2022-128815
000117609 041__ $$aeng
000117609 100__ $$0(orcid)0000-0001-8219-2365$$aCabeza-Gil, Iulen$$uUniversidad de Zaragoza
000117609 245__ $$aAutomated segmentation of the ciliary muscle in OCT images using fully convolutional networks
000117609 260__ $$c2022
000117609 5060_ $$aAccess copy available to the general public$$fUnrestricted
000117609 5203_ $$aQuantifying 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.
000117609 536__ $$9info:eu-repo/grantAgreement/ES/MICINN/PID2020-113822RB-C12$$9info:eu-repo/grantAgreement/ES/MICIU/PRE2018-084021
000117609 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000117609 590__ $$a3.4$$b2022
000117609 592__ $$a0.955$$b2022
000117609 591__ $$aBIOCHEMICAL RESEARCH METHODS$$b28 / 77 = 0.364$$c2022$$dQ2$$eT2
000117609 593__ $$aBiotechnology$$c2022$$dQ1
000117609 591__ $$aRADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING$$b43 / 135 = 0.319$$c2022$$dQ2$$eT1
000117609 593__ $$aAtomic and Molecular Physics, and Optics$$c2022$$dQ1
000117609 591__ $$aOPTICS$$b36 / 99 = 0.364$$c2022$$dQ2$$eT2
000117609 594__ $$a6.7$$b2022
000117609 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000117609 700__ $$aRuggeri, Marco
000117609 700__ $$aChang, Yu-Cherng
000117609 700__ $$0(orcid)0000-0001-9713-1813$$aCalvo, Begoña$$uUniversidad de Zaragoza
000117609 700__ $$aManns, Fabrice
000117609 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000117609 773__ $$g13, 5 (2022), 2810-2823$$pBIOMEDICAL OPTICS EXPRESS$$tBiomedical Optics Express$$x2156-7085
000117609 8564_ $$s6100333$$uhttps://zaguan.unizar.es/record/117609/files/texto_completo.pdf$$yVersión publicada
000117609 8564_ $$s2510141$$uhttps://zaguan.unizar.es/record/117609/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000117609 909CO $$ooai:zaguan.unizar.es:117609$$particulos$$pdriver
000117609 951__ $$a2024-03-18-13:08:38
000117609 980__ $$aARTICLE