Conference Proceeding

Microaneurysms detection using a novel neighborhood analysis

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Abstract

The earliest sign of the diabetic retinopathy is the appearance of small red dots in retinal fundus images, designated by microaneurysms. In this paper a scale-space based method is proposed for the microaneurysms detection. Initially, the method performs a segmentation of the retinal vasculature and defines a global set of microaneurysms candidates, using both coarser and finer scales. Using the finer scales, a set of microaneurysms candidates are analysed in terms of shape and size. Then, a set of gaussian-shaped matched filters are used to reduce the number of false microaneurysms candidates. Each candidate is labeled as a true microaneurysm using a new neighborhood analysis method. The proposed algorithm was tested with the training Retinopathy Online Challenge (ROC) dataset, revealing a 47% Sensitivity with an average number of 37.9 false positives per image.

How to Cite:

Soares, I. & Castelo-Branco, M. & Pinheiro, A. M., (2014) “Microaneurysms detection using a novel neighborhood analysis”, Proceedings of the Ophthalmic Medical Image Analysis International Workshop 1(2014), 65-72. doi: https://doi.org/10.17077/omia.1010

Rights: Copyright © 2014, Ivo Soares, Miguel Castelo-Branco and Antonio M.G. Pinheiro.