Year: 2024
Type: book-chapter
Abstract: This study presents an optimized multi-level thresholding technique for the retinal vessel segmentation in fundus images. The proposed methodology involves pre-processing steps such as illumination compensation and adaptive histogram equalization to enhance vessel visibility. The segmentation is performed using a Tsallis-based multi-level thresholding algorithm, and the results are evaluated using ground truth images. Performance metrics including sensitivity, specificity, and accuracy are calculated, demonstrating the effectiveness of the proposed method in detecting blood vessels accurately. The average values of specificity, sensitivity and are found to be higher compared to an existing method. The proposed technique also shows promising results in differentiating normal and abnormal retinal images.
Source: CRC Press eBooks
Authors: Vishali Shapar, Jyoti Rani
Institution: Maharaja Ranjit Singh Punjab Technical University
Language: English
Topic: Retinal Imaging and Analysis
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4399582001