Automatic Hemorrhages Detection Based on Fundus Images

This paper proposes methods to detect hemorrhages which are known as a kind of lesions in diabetic retinopathy. To detect the symptom, eye fundus structures (blood vessels and fovea) as well as microaneuysms need to be discriminated to filter out only the hemorrhages. Five processing steps are proposed based analysis on fundus images. First, preprocessing step is processed to improve the quality of the image. Then all red features are filtered out. They include blood vessels, fovea, microaneurysms and hemorrhages. After that, morphology operation and compactness measurement are applied to eliminate the fovea, and blood vessels. Finally, hemorrhages can be classified by using area method to remove microaneurysms and some small noise. 579 fundus images from Bhumibol Adulyadej Hospital were tested. The results were analysis by ophthalmologist in order to define system accuracy and preciseness. According to results of comparison, we found that the accuracy is 90 % and the average of processing time is 6.23 seconds per image.