Abstract: The detection of exudates is a prerequisite for detecting and grading severe retinal lesions, like the diabetic macular edema. In this work, we present a new method based on mathematical morphology for detecting exudates in color eye fundus images. A preliminary evaluation of the proposed method performance on a known public database, namely DIARETDB1, indicates that it can achieve an average sensitivity of 70.48%, and an average specificity of 98.84%. Comparing to other recent automatic methods available in the literature, our proposed approach potentially can obtain better exudate detection results in terms of sensitivity and specificity. (Source: Computerized Medical Imaging and Graphics)

Further information:

Article source

Related posts:

1. A novel method for blood vessel detection from retinal images
2. Ovarian cancer classification based on dimensionality reduction for SELDI-TOF data
3. Three-dimensional coupled-object segmentation using symmetry and tissue type information
4. Automated detection of near falls: algorithm development and preliminary results
5. Incremental value of contrast myocardial perfusion to detect intermediate versus severe coronary artery stenosis during stress-echocardiography.