Algorithmic Analysis of Vesselness and Blobness for Detecting Retinopathies Based on Fractional Gaussian Filters

Maria de Jesus Estudillo-Ayala, Hugo Aguirre-Ramos, Juan Gabriel Avina-Cervantes, Jorge Mario Cruz-Duarte, Ivan Cruz-Aceves and Jose Ruiz-Pinales
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Maria de Jesus Estudillo-Ayala: School of Biological Systems and Technological Innovation, Benito Juárez Autonomous University of Oaxaca, Oaxaca 68020, Mexico
Hugo Aguirre-Ramos: Telematics (CA), Engineering Division (DICIS), Campus Irapuato-Salamanca, University of Guanajuato, Carretera Salamanca-Valle de Santiago km 3.5 + 1.8km, Comunidad de Palo Blanco, Salamanca 36885, Mexico
Juan Gabriel Avina-Cervantes: Telematics (CA), Engineering Division (DICIS), Campus Irapuato-Salamanca, University of Guanajuato, Carretera Salamanca-Valle de Santiago km 3.5 + 1.8km, Comunidad de Palo Blanco, Salamanca 36885, Mexico
Jorge Mario Cruz-Duarte: Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Col. Tecnológico, Monterrey 64849, Nuevo León, Mexico
Ivan Cruz-Aceves: CONACYT Research-Fellow, Center for Research in Mathematics (CIMAT), A.C., Jalisco S/N, Col. Valenciana, Guanajuato 36000, Mexico
Jose Ruiz-Pinales: Telematics (CA), Engineering Division (DICIS), Campus Irapuato-Salamanca, University of Guanajuato, Carretera Salamanca-Valle de Santiago km 3.5 + 1.8km, Comunidad de Palo Blanco, Salamanca 36885, Mexico

Mathematics, 2020, vol. 8, issue 5, 1-19

Abstract: All around the world, partial or total blindness has become a direct consequence of diabetes and hypertension. Visual disorders related to these diseases require automatic and specialized methods to detect early malformations, artifacts, or irregular structures for helping specialists in the diagnosis. This study presents an innovative methodology for detecting and evaluating retinopathies, particularly microaneurysm and hemorrhages. The method is based on a multidirectional Fractional-Order Gaussian Filters tuned by the Differential Evolution algorithm. The contrast of the microaneurysms and hemorrhages, regarding the background, is improved substantially. After that, these structures are extracted using the Kittler thresholding method under additional considerations. Then, candidate lesions are detected by removing the blood vessels and fovea pixels in the resulting image. Finally, candidate lesions are classified according to its size, shape, and intensity properties via Support Vector Machines with a radial basis function kernel. The proposed method is evaluated by using the publicly available database MESSIDOR for detecting microaneurysms. The numerical results are summarized by the averaged binary metrics of accuracy, sensitivity, and specificity giving the performance values of 0.9995, 0.7820 and 0.9998, respectively.

Keywords: fractional calculus; gaussian filtering; differential evolution; retinal microaneurysm; diabetic retinopathy; MESSIDOR Image Database (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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