Conference Paper/Proceeding/Abstract 1140 views
Segmentation and Tracking of Coronary Arterial Wall
Ehab Essa,
Xianghua Xie 
Computational and Mathematical Biomedical Engineering
Swansea University Author:
Xianghua Xie
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Abstract
In this paper, we present a segmentation and tracking method based on hidden Markov model (HMM) to detect the outer coronary arterial wall in intravascular images. The proposed method tracks a set of hidden states representing the border location on a set of normal lines obtained from the previ- ous...
| Published in: | Computational and Mathematical Biomedical Engineering |
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| ISSN: | 2227-3085 2227-9385 |
| Published: |
2017
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa32107 |
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| Abstract: |
In this paper, we present a segmentation and tracking method based on hidden Markov model (HMM) to detect the outer coronary arterial wall in intravascular images. The proposed method tracks a set of hidden states representing the border location on a set of normal lines obtained from the previ- ous frame. The border observation is derived from a classification-based cost function and a shape prior model. The emission probability is defined based on two Gaussian probability distributions for the vessel border and background. The transition probability is learned by using the Baum-Welch algorithm. The optimal sequence of the hidden states is obtained by using Viterbi algorithm. The proposed method shows promising results on tracking and segmenting the arterial wall. |
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| Item Description: |
The paper is available freely online as part of CMBE 2017 Proceedings Vol. 1: http://www.compbiomed.net/2017/cmbe-proceedings.htm |
| Keywords: |
Image analysis, machine learning |
| College: |
Faculty of Science and Engineering |