Boundary Detection in Echocardiographic Images Using Markovian Level Set Method
Summary :
Owing to the large amount of speckle noise and ill-defined edges present in echocardiographic images, computer-based boundary detection of the left ventricle has proved to be a challenging problem. In this paper, a Markovian level set method for boundary detection in long-axis echocardiographic images is proposed. It combines Markov random field (MRF) model, which makes use of local statistics with level set method that handles topological changes, to detect a continuous and smooth boundary. Experimental results show that higher accuracy can be achieved with the proposed method compared with two related MRF-based methods.
- Publication
- IEICE TRANSACTIONS on Information Vol.E90-D No.8 pp.1292-1300
- Publication Date
- 2007/08/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e90-d.8.1292
- Type of Manuscript
- PAPER
- Category
- Image Recognition, Computer Vision
Authors
Keyword
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Jierong CHENG, Say-Wei FOO, "Boundary Detection in Echocardiographic Images Using Markovian Level Set Method" in IEICE TRANSACTIONS on Information,
vol. E90-D, no. 8, pp. 1292-1300, August 2007, doi: 10.1093/ietisy/e90-d.8.1292.
Abstract: Owing to the large amount of speckle noise and ill-defined edges present in echocardiographic images, computer-based boundary detection of the left ventricle has proved to be a challenging problem. In this paper, a Markovian level set method for boundary detection in long-axis echocardiographic images is proposed. It combines Markov random field (MRF) model, which makes use of local statistics with level set method that handles topological changes, to detect a continuous and smooth boundary. Experimental results show that higher accuracy can be achieved with the proposed method compared with two related MRF-based methods.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e90-d.8.1292/_p
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@ARTICLE{e90-d_8_1292,
author={Jierong CHENG, Say-Wei FOO, },
journal={IEICE TRANSACTIONS on Information},
title={Boundary Detection in Echocardiographic Images Using Markovian Level Set Method},
year={2007},
volume={E90-D},
number={8},
pages={1292-1300},
abstract={Owing to the large amount of speckle noise and ill-defined edges present in echocardiographic images, computer-based boundary detection of the left ventricle has proved to be a challenging problem. In this paper, a Markovian level set method for boundary detection in long-axis echocardiographic images is proposed. It combines Markov random field (MRF) model, which makes use of local statistics with level set method that handles topological changes, to detect a continuous and smooth boundary. Experimental results show that higher accuracy can be achieved with the proposed method compared with two related MRF-based methods.},
keywords={},
doi={10.1093/ietisy/e90-d.8.1292},
ISSN={1745-1361},
month={August},}
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TY - JOUR
TI - Boundary Detection in Echocardiographic Images Using Markovian Level Set Method
T2 - IEICE TRANSACTIONS on Information
SP - 1292
EP - 1300
AU - Jierong CHENG
AU - Say-Wei FOO
PY - 2007
DO - 10.1093/ietisy/e90-d.8.1292
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E90-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2007
AB - Owing to the large amount of speckle noise and ill-defined edges present in echocardiographic images, computer-based boundary detection of the left ventricle has proved to be a challenging problem. In this paper, a Markovian level set method for boundary detection in long-axis echocardiographic images is proposed. It combines Markov random field (MRF) model, which makes use of local statistics with level set method that handles topological changes, to detect a continuous and smooth boundary. Experimental results show that higher accuracy can be achieved with the proposed method compared with two related MRF-based methods.
ER -
English
