An automatic cognitive graph-based segmentation for detection of blood vessels in retinal images

DOI10.1155/2016/7906165zbMath1400.94006OpenAlexW2398774141WikidataQ59141230 ScholiaQ59141230MaRDI QIDQ1793589

Prashanth Reddy Marpu, Rasha Al Shehhi, Wei Lee Woon

Publication date: 12 October 2018

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2016/7906165

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Uses Software

• DIARETDB1

Cites Work

• Unnamed Item
• Retinal vessel segmentation using a probabilistic tracking method
• Efficient graph-based image segmentation
• A general approach to connected-component labeling for arbitrary image representations
• Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation
• Including the Size of Regions in Image Segmentation by Region-Based Graph
• An Automatic Graph-Based Approach for Artery/Vein Classification in Retinal Images
• Linear-time connected-component labeling based on sequential local operations
• Constructive Links between Some Morphological Hierarchies on Edge-Weighted Graphs
• Discovering Knowledge in Data
• Scale Space and PDE Methods in Computer Vision

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