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Automatic vessel network features quantification using local vessel pattern operator

delete2013-06-01
delete18
PRE
AI
A
Abdolhossein Fathi *
A
Ahmad Reza Naghsh‐Nilchi
F
Fardin Abdali-Mohammadi
DOI:10.1016/j.compbiomed.2013.01.011delete
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Abstract

Abstract

En 中文
Automatic measurement and quantification of blood vessels' features and detection of vessel landmarks are key steps in the computer-aided diagnosis and diseases monitoring. This work proposes a novel and robust method for detecting vessel landmarks, i.e. bifurcation and crossovers, and measurement of different features, i.e. vessel orientation and vessel diameter as well as bifurcation angle, from the detected vessel network using simple and efficient local vessel pattern operator. The proposed method is applied to the publicly available DRIVE, STARE and ARIA databases and compared with existing state-of-the-art approaches. It shows higher accuracy in detection of vessel landmark and estimation of vessel features. (C) 2013 Elsevier Ltd. All rights reserved.
Keywords:
Vessel orientation detection
Vessel diameter estimation
Vessel landmark detection
Local vessel pattern operator
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Journal

Computers in Biology and Medicine cover
Computers in Biology and Medicine
IF:
6.3
Papers:
8.3K
Citations:
3.3W

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U
University of Isfahan
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Papers: 4.1K
Citations: 5