Vessel Extractio Techniques and Algorithms: A Survey

Authors:
Cemil Kirbas;Francis K. H. Quek
Affiliations:
-;-
Venue:
BIBE '03 Proceedings of the 3rd IEEE Symposium on BioInformatics and BioEngineering
Year:
2003

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Abstract

Vessel segmentation algorithms are critical components of circulatory blood vessel analysis systems. We present a survey of vessel extraction techniques and algorithms, putting the various approaches and techniques in perspective by means of a classification of the existing research. While we target mainly the extraction of blood vessels, neurosvascular structure in particular, we also review some of the segmentation methods for the tubular objects that showsimilar characteristics to vessels. We divide vessel segmentation algorithms and techniques into six main categories: (1) pattern recognition techniques, (2) model-based approaches, (3) tracking-based approaches, (4) artificial intelligence-based approaches, (5) neural network-based approaches, and (6) miscellaneous tube-like object detection approaches. Some of these categories are further divided into sub-categories. A table compares the papersagainst such criteria as dimensionality, input type, preprocessing, user interaction, and result type.