Microaneurysm Detection in Fundus Images Using a Two-Step Convolutional Neural Network
Published in Biomedical Engineering Online, 2019
This paper introduces a two-step convolutional neural network for automated detection of microaneurysms in fundus images, a critical early marker of diabetic retinopathy. The method enhances diagnostic accuracy by combining image processing and deep learning to identify microaneurysm lesions with high sensitivity and specificity.
Recommended citation: N. Eftekhari, H. Pourreza, M. Masoudi, K. G. Shirazi, and E. Saeedi, "Microaneurysm detection in fundus images using a two-step convolutional neural network," Biomedical Engineering Online, 2019.
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