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dc.contributor.authorMello Román, Julio César
dc.contributor.authorVázquez Noguera, José Luis 
dc.contributor.authorGarcía Torres, Miguel
dc.contributor.authorCastillo, Veronica Elisa
dc.contributor.authorCastro Matto, Ingrid
dc.contributor.otherUniversidad Nacional de Concepción - Facultad de Medicina (PY)es
dc.contributor.otherUniversidad Pablo de Olavide (ES)es
dc.date.accessioned2022-04-29T23:13:33Z
dc.date.available2022-04-29T23:13:33Z
dc.date.issued2020
dc.identifier.urihttp://hdl.handle.net/20.500.14066/3797
dc.description.abstractRetinal images are widely used for diagnosis and eye disease detection. However, due to the acquisition process, retinal images often have problems such as low contrast, blurry details or artifacts. These problems may severely affect the diagnosis. Therefore, it is very impor tant to enhance the visual quality of such images. Contrast enhancement is a pre-processing applied to images to improve their visual quality. This technique betters the identification of retinal structures in degraded reti nal images. In this work, a novel algorithm based on multi-scale mathe matical morphology is presented. First, the original image is blurred us ing the Open-Close Close-Open (OCCO) filter to reduce any artifacts in the image. Next, multiple bright and dark features are extracted from the filtered image by the Top-Hat transform. Finally, the maximum bright values are added to the original image and the maximum dark values are subtracted from the original image, previously adjusted by a weight. The algorithm was tested on 397 retinal images from the public STARE database. The proposed algorithm was compared with state of the art al gorithms and results show that the proposal is more efficient in improving contrast, maintaining similarity with the original image and introducing less distortion than the other algorithms. According to ophthalmologists, the algorithm, by improving retinal images, provides greater clarity in the blood vessels of the retina and would facilitate the identification of pathologies.es
dc.description.sponsorshipCONACYT - Consejo Nacional de Ciencia y Tecnologíaes
dc.language.isoenges
dc.subject.classification1303 I+D en relación con las Ciencias médicases
dc.subject.otherRETINAL IMAGESes
dc.subject.otherCONTRAST ENHANCEMENTes
dc.subject.otherMATHEMATICAL MOR PHOLOGYes
dc.subject.otherTOP-HAT TRANSFORMes
dc.titleRetinal image enhancement via a multiscale morphological approach with OCCO filter.es
dc.typeresearch articlees
dc.identifier.doi10.1007/978-3-030-68285-9_18es
dc.description.fundingtextPROCIENCIAes
dc.issue.number186es
dc.journal.titleInformation Technology and Systemses
dc.relation.projectCONACYTPINV18-846es
dc.rights.accessRightsopen accesses
dc.volume.number177es


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