Retinopathy online challenge: automatic detection of microaneurysms in digital color fundus photographsReport as inadecuate




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1 Department of ophthalmology & visual sciences 2 ISI - Image sciences institute - University of Utrecht 3 Department of engineering 4 Department of intelligent image information 5 ITI - Département Image et Traitement Information 6 LaTIM - Laboratoire de Traitement de l-Information Medicale 7 GIB - Biomedical engineering group 8 Department of electrical and computer engineering 9 UBO - Université de Brest 10 School of Computer Science and Technology Harbin 11 Department of computing 12 Department of statistics and operative investigation 13 Department of electronic systems engineering 14 CHRU Brest - Centre Hospitalier Régional Universitaire de Brest 15 Department of Electrical and Computer Engineering U. of Iowa

Abstract : The detection of microaneurysms in digital color fundus photographs is a critical first step in automated screening for diabetic retinopathy DR, a common complication of diabetes. To accomplish this detection numerous methods have been published in the past but none of these were compared with each other on the same data. In this work we present the results of the first international microaneurysm detection competition, organized in the context of the Retinopathy Online Challenge ROC, a multiyear online competition for various aspects of DR detection. For this competition, we compare the results of five different methods, produced by five different teams of researchers on the same set of data. The evaluation was performed in a uniform manner using an algorithm presented in this work. The set of data used for the competition consisted of 50 training images with available reference standard and 50 test images where the reference standard was witheld by the organizers MN, BVG and MDA. The results obtained on the test data was submitted through a website after which standardized evaluation software was used to determine the performance of each of the methods. A human expert detected microaneurysms in the test set to allow comparison with the performance of the automatic methods. The overall results show that microaneurysm detection is a challenging task for both the automatic methods as well as the human expert. There is room for improvement as the best performing system does not reach the performance of the human expert. The data associated with the ROC microaneurysm detection competition will remain publicly available and the website will continue accepting submissions.

Keywords : Computer aided detection Computer aided diagnosis Diabetic retinopathy Fundus photographs Retina ROC competition





Author: Meindert Niemeijer - Bram Van Ginneken - Michael J. Cree - Atsushi Mizutani - Gwénolé Quellec - Clara I. Sanchez - Bob Zhang -

Source: https://hal.archives-ouvertes.fr/



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