Mostrar o rexistro simple do ítem
Fully automatic segmentation and monitoring of choriocapillaris flow voids in OCTA images
dc.contributor.author | López-Varela, Emilio | |
dc.contributor.author | Moura, Joaquim de | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Fernández-Vigo, José Ignacio | |
dc.contributor.author | Moreno-Morillo, Francisco Javier | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.date.accessioned | 2023-03-27T12:40:51Z | |
dc.date.available | 2023-03-27T12:40:51Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | E. López-Varela, J. de Moura, J. Novo, J.I. Fernández-Vigo, F.J. Moreno-Morillo, & M. Ortega, "Fully automatic segmentation and monitoring of choriocapillaris flow voids in OCTA images", Computerized Medical Imaging and Graphics, 104, 2023, doi:10.1016/j.compmedimag.2022.102172. | es_ES |
dc.identifier.uri | http://hdl.handle.net/2183/32778 | |
dc.description | Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG. | es_ES |
dc.description.abstract | [Abstract]: Optical coherence tomography angiography (OCTA) is a non-invasive ophthalmic imaging modality that is widely used in clinical practice. Recent technological advances in OCTA allow imaging of blood flow deeper than the retinal layers, at the level of the choriocapillaris (CC), where a granular image is obtained showing a pattern of bright areas, representing blood flow, and a pattern of small dark regions, called flow voids (FVs). Several clinical studies have reported a close correlation between abnormal FVs distribution and multiple diseases, so quantifying changes in FVs distribution in CC has become an area of interest for many clinicians. However, CC OCTA images present very complex features that make it difficult to correctly compare FVs during the monitoring of a patient. In this work, we propose fully automatic approaches for the segmentation and monitoring of FVs in CC OCTA images. First, a baseline approach, in which a fully automatic segmentation methodology based on local contrast enhancement and global thresholding is proposed to segment FVs and measure changes in their distribution in a straightforward manner. Second, a robust approach in which, prior to the use of our segmentation methodology, an unsupervised trained neural network is used to perform a deformable registration that aligns inconsistencies between images acquired at different time instants. The proposed approaches were tested with CC OCTA images collected during a clinical study on the response to photodynamic therapy in patients affected by chronic central serous chorioretinopathy (CSC), demonstrating their clinical utility. The results showed that both approaches are accurate and robust, surpassing the state of the art, therefore improving the efficacy of FVs as a biomarker to monitor the patient treatments. This gives great potential for the clinical use of our methods, with the possibility of extending their use to other pathologies or treatments associated with this type of imaging. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED481B-2021-059 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2020/24 | es_ES |
dc.description.sponsorship | Xunta de Galicia; IN845D 2020/38 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.description.sponsorship | This research was funded by Instituto de Salud Carlos III, Government of Spain, DTS18/00136 research project; Ministerio de Ciencia e Innovación y Universidades, Government of Spain, RTI2018-095894-B-I00 research project; Ministerio de Ciencia e Innovación, Government of Spain through the research projects with references PID2019-108435RB-I00; TED2021-131201B-I00 and PDC2022-133132-I00; Consellería de Cultura, Educación e Universidade, Xunta de Galicia through the postdoctoral, grant ref. ED481B-2021-059; and Grupos de Referencia Competitiva, grant ref. ED431C 2020/24; Axencia Galega de Innovación (GAIN), Xunta de Galicia, grant ref. IN845D 2020/38; CITIC, as Research Center accredited by Galician University System, is funded by “Consellería de Cultura, Educación e Universidade from Xunta de Galicia”, supported in an 80 % through ERDF Funds, ERDF Operational Programme Galicia 2014–2020, and the remaining 20 % by “Secretaría Xeral de Universidades”, grant ref. ED431G 2019/01. Emilio López Varela acknowledges its support under FPI Grant Program through PID2019-108435RB-I00 project. Funding for open access charge: Universidade da Coruña/CISUG. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info:eu-repo/grantAgreement/ISCIII/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DTS18%2F00136/ES/PLATAFORMA ONLINE PARA PREVENCION Y DETECCION PRECOZ DE ENFERMEDAD VASCULAR MEDIANTE ANALISIS AUTOMATIZADO DE INFORMACION E IMAGEN CLINICA | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095894-B-I00/ES/DESARROLLO DE TECNOLOGIAS INTELIGENTES PARA DIAGNOSTICO DE LA DMAE BASADAS EN EL ANALISIS AUTOMATICO DE NUEVAS MODALIDADES HETEROGENEAS DE ADQUISICION DE IMAGEN OFTALMOLOGICA | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108435RB-I00/ES/CUANTIFICACION Y CARACTERIZACION COMPUTACIONAL DE IMAGEN MULTIMODAL OFTALMOLOGICA: ESTUDIOS EN ESCLEROSIS MULTIPLE | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2024/TED2021-131201B-I00/ES/ | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2024/PDC2022-133132-I00/ES/ | es_ES |
dc.relation.uri | https://doi.org/10.1016/j.compmedimag.2022.102172 | es_ES |
dc.rights | Atribución 4.0 Internacional (CC BY 4.0) | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Central Serous Chorioretinopathy | es_ES |
dc.subject | Choriocapillaris | es_ES |
dc.subject | Flow voids | es_ES |
dc.subject | OCTA imaging | es_ES |
dc.subject | Photodynamic Therapy | es_ES |
dc.title | Fully automatic segmentation and monitoring of choriocapillaris flow voids in OCTA images | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Computerized Medical Imaging and Graphics | es_ES |
UDC.issue | 104 | es_ES |
dc.identifier.doi | 10.1016/j.compmedimag.2022.102172 |
Ficheiros no ítem
Este ítem aparece na(s) seguinte(s) colección(s)
-
GI-VARPA - Artigos [75]