Show simple item record

dc.creatorEscorcia-Gutierrez, Jose
dc.creatorTorrents-Barrena, Jordina
dc.creatorGamarra, Margarita
dc.creatorRomero-Aroca, Pedro
dc.creatorValls, Aida
dc.creatorPuig, Domenec
dc.date.accessioned2021-04-07T13:52:18Z
dc.date.available2021-04-07T13:52:18Z
dc.date.issued2021-07-15
dc.identifier.issn0957-4174
dc.identifier.urihttps://hdl.handle.net/11323/8083
dc.description.abstractRetinal disorders are a severe health threat for older adults because they may lead to vision loss and blindness. Diabetic patients are particularly prone to suffer from Diabetic Retinopathy. Identifying relevant structural components in color fundus images like the optic disc (OD) is crucial to diagnose retinal diseases. Automatic OD detection is complex because of its location in an area where blood vessels converge, and color distribution is uneven. Several image processing techniques have been developed for OD detection so far, but vessel segmentation is sometimes required, increasing computational complexity and time. Moreover, precise OD segmentation methods utilize complex algorithms that need special hardware or extensive labeled datasets. We propose an OD detection approach based on the Modern Portfolio Theory of Markowitz to generate an innovative color fusion model. Specifically, the training phase calculates the optimal weights for each color channel. A fusion of weighted color channels is then applied in the testing phase. This approach acts as a powerful and real-time preprocessing stage. We use four heterogeneous datasets to validate the presented methodology. Three out of four datasets are publicly available (i.e., DRIVE, Messidor, and HRF), and the last corresponds to an in–house dataset acquired from Hospital Universitari Sant Joan de Reus (Spain). Two different segmentation methods are presented and compared with state-of-the-art computer vision techniques to analyze the model performance. An outstanding accuracy and overlap above 0.9 and 80%, respectively, and a minimal execution time of 0.05 s are reached. Therefore, our model could be integrated into daily clinical practice to accelerate the diagnosis of Diabetic Retinopathy due to its simplicity, performance, and speed.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherCorporación Universidad de la Costaspa
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.sourceExpert Systems with Applicationsspa
dc.subjectDiabetic retinopathyspa
dc.subjectOptic discspa
dc.subjectColor fusiónspa
dc.subjectMarkowitz portfoliospa
dc.subjectSegmentationspa
dc.titleA color fusion model based on Markowitz portfolio optimization for optic disc segmentation in retinal imagesspa
dc.typePreprintspa
dc.source.urlhttps://www.sciencedirect.com/science/article/abs/pii/S095741742100138X?utm_campaign=STMJ_AUTH_SERV_PUBLISHED&utm_medium=email&utm_acid=148664364&SIS_ID=&dgcid=STMJ_AUTH_SERV_PUBLISHED&CMX_ID=&utm_in=DM129530&utm_source=AC_spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doihttps://doi.org/10.1016/j.eswa.2021.114697
dc.date.embargoEnd2023-07-19
dc.type.hasversioninfo:eu-repo/semantics/draftspa


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record

CC0 1.0 Universal
Except where otherwise noted, this item's license is described as CC0 1.0 Universal