A retinography image analysis and processing system as a support tool for detecting silent cerebral infarction
The aim of this project is to develop an image analysis software tool able to identify, extract and quantify anatomical features from eye fundus images for use as part of clinical research processes. In the case of this project, the objective of these research processes will be to identify and correlate different anomalies that may be detected in the retinal micro-vascular system with occurrence and/or early diagnosis of silent cerebral infarction.
The main goal of Retinal project is to provide specialist clinical staff with new image viewing and analysis tools to improve silent stroke detection and diagnosis processes. More specifically, it aims at implementing mechanisms for processing and for automatic and semi-automatic extraction of the characteristics of images of the back of the eye (fundus) as a potential target for detecting disease at an early stage. Together with other decision support systems such as brain magnetic resonance imaging (MRI), these tools will determine relationships and/or correlations between brain damage patients and those with damage or changes in micro-vascularisation of the retina.