Zero-crossing interval correction in tracing eye-fundus blood vessels
Pattern Recognition
ISMDA '01 Proceedings of the Second International Symposium on Medical Data Analysis
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Digital Image Processing Using MATLAB
Digital Image Processing Using MATLAB
ICCSIT '08 Proceedings of the 2008 International Conference on Computer Science and Information Technology
Journal of Medical Systems
A Decision Support System for Automatic Screening of Non-proliferative Diabetic Retinopathy
Journal of Medical Systems
A Sorting System for Hierarchical Grading of Diabetic Fundus Images: A Preliminary Study
IEEE Transactions on Information Technology in Biomedicine
Journal of Medical Systems
Automated detection of exudates and macula for grading of diabetic macular edema
Computer Methods and Programs in Biomedicine
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Due to increasing number of diabetic retinopathy cases, ophthalmologists are experiencing serious problem to automatically extract the features from the retinal images. Optic disc (OD), exudates, and cotton wool spots are the main features of fundus images which are used for diagnosing eye diseases, such as diabetic retinopathy and glaucoma. In this paper, a new algorithm for the extraction of these bright objects from fundus images based on marker-controlled watershed segmentation is presented. The proposed algorithm makes use of average filtering and contrast adjustment as preprocessing steps. The concept of the markers is used to modify the gradient before the watershed transformation is applied. The performance of the proposed algorithm is evaluated using the test images of STARE and DRIVE databases. It is shown that the proposed method can yield an average sensitivity value of about 95%, which is comparable to those obtained by the known methods.