Automated Detection of Vascular Lesions in Fluorescein Angiography Retinal Images by Image Processing Methods

por Meysam Tavakoli (I-image Analysis Group, Mashad University of Medical Science/ Ferdowsy University of Mashad (Irán))

lunes 7 nov. 2011 12:30 → 13:30 Europe/Madrid

Sala de Audiovisuales (Nave experimental del IFIC)

Early detection of microaneurysms (MAs), the first sign of Diabetic Retinopathy (DR), is an essential first step in automated detection of DR to prevent vision loss and blindness. This study presents a novel and different algorithm for automatic detection of MAs in fluorescein angiography fundus images, based on Radon transform (RT) and multi-overlapping windows. This project addresses a novel method, in detection of retinal land marks and lesions to diagnose the DR. At the first step, optic nerve head (ONH) was detected and masked. In preprocessing stage, top-hat transformation and averaging filter were applied to remove the background. In main processing section, firstly, we divided the whole preprocessed image into sub-images and then we segmented and masked the vascular tree by applying RT in each sub-image. After detecting and masking retinal vessels and ONH, MAs were detected and numbered by using RT and appropriated thresholding. The results of the proposed method were evaluated reported on two different retinal images databases, the Mashhad Database with 120 fluorescein angiography (FA) fundus images and Second Local Database from Tehran with 50 FA retinal images. Automated DR detection demonstrated a sensitivity and specificity of 94% and 75% for Mashhad database and 100% and 70% for the Second Local Database respectively.