Title: Hybrid multi-kernel SVM algorithm for microaneurysm recognition in colour fundus images

Authors: S.B. Mohan; B. Kannan; D. Ravikumar; C. Sivakumaran

Addresses: Department of Electronics and Communication Engineering, S.A. Engineering College, Chennai, Tamilnadu, India ' Department of Electronics and Communication Engineering, Ramco Institute of Technology, Rajapalayam, India ' Department of Electronics and Communication Engineering, Kings Engineering College, Chennai, India ' Photon Technologies, Chennai, India

Abstract: Diabetic retinopathy (DR) is a condition that results in impaired vision and is triggered by diabetic. These alterations in the retinal vessels may be traced back to hyperglycemia. Microaneurysms (MAs) seem to be the initial disease symptoms of DR, and a prompt identification of microaneurysms may assist in the detection of DR in the preclinical phase. Optical coherence imaging system, often known as OCT, is a non-invasive imaging technology that offers a cross-sectional picture of the retinal. We construct new probability foundations for support vector machines (SVMs) using informational differences and the Fisher score. The findings that were achieved were as follows: the accuracy criterion had a score of 96.32%, the sensitivity criterion had a score of 97.34%, the specificity criterion had a score of 95.42%, and the precision criterion had a score of 95.27%.

Keywords: retinal pictures; scaled Dirichlet combination; support vector machines; SVMs; microaneurysm images.

DOI: 10.1504/IJMEI.2025.147585

International Journal of Medical Engineering and Informatics, 2025 Vol.17 No.4, pp.370 - 381

Received: 28 Aug 2022
Accepted: 03 Dec 2022
Published online: 24 Jul 2025 *

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