Microaneurysm detection in color eye fundus images for diabetic retinopathy screening

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Melo, T (Author) Other; Ana Maria Mendonça (Author) FEUP; Aurélio Campilho (Author) FEUP

Journal

Title: Computers in Biology and Medicine

Vol. 126

ISSN: 0010-4825

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 10 Citations

Scopus - 14 Citations

Other information

Authenticus ID: P-00S-R9A

DOI: 10.1016/j.compbiomed.2020.103995

Abstract (EN): Diabetic retinopathy (DR) is a diabetes complication, which in extreme situations may lead to blindness. Since the first stages are often asymptomatic, regular eye examinations are required for an early diagnosis. As microaneurysms (MAs) are one of the first signs of DR, several automated methods have been proposed for their detection in order to reduce the ophthalmologists' workload. Although local convergence filters (LCFs) have already been applied for feature extraction, their potential as MA enhancement operators was not explored yet. In this work, we propose a sliding band filter for MA enhancement aiming at obtaining a set of initial MA candidates. Then, a combination of the filter responses with color, contrast and shape information is used by an ensemble of classifiers for final candidate classification. Finally, for each eye fundus image, a score is computed from the confidence values assigned to the MAs detected in the image. The performance of the proposed methodology was evaluated in four datasets. At the lesion level, sensitivities of 64% and 81% were achieved for an average of 8 false positives per image (FPIs) in e-ophtha MA and SCREEN-DR, respectively. In the last dataset, an AUC of 0.83 was also obtained for DR detection.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 14