Segmentation of Retinal Vasculature using Active Contour Models (Snakes)

• Main Author: Pang, Kee Y ong
• Format: Final Year Project
• Language: English
• Published: Universiti Teknologi Petronas 2009
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://utpedia.utp.edu.my/8926/1/2009%20Bachelor%20-%20Segmentation%20Of%20Retinal%20Vasculature%20Using%20Active%20Control%20Model%20%28SNAKE%29.pdf; http://utpedia.utp.edu.my/8926/

Characteristic of retinal vasculature has been an important indicator for many diseases such as hypertension and diabetes. A digital image analysis system can assist medical experts to make accurate diagnosis in an efficient manner. This project presents the computer based approach to the automated segmentation of blood vessels in retinal images. The detection of the retinal vessel is achieved by performing image enhancement using CLAHE followed by Bottom-hat morphological transformation. Active contour model (snake) that based on level sets, techniques of curve evolution, and Mumford-Shah functional for segmentation is then used to segment out the detected retinal vessel and produce a complete retinal vasculature. A Graphic User Interface (GUI) has also been created to ease the user for the segmentation of the retinal vasculature. The algorithm is then tested with 20 test images from the DRIVE database. The results shows that the algorithm outperforms many other published methods and achieved an accuracy (ability to detect both vessel and non-vessel pixels) range of 0.92-0.94, a sensitivity (ability to detect vessel pixels) range of 0.91-0.95 and a specificity (ability to detect non-vessel pixels) range of0.78-0.85. IV