Fast segmentation of ultrasound images using robust Rayleigh distribution decomposition

被引:20
作者
Ahn, Chi Young [1 ]
Jung, Yoon Mo [1 ]
Kwon, Oh In [2 ]
Seo, Jin Keun [1 ]
机构
[1] Yonsei Univ, Dept Computat Sci & Engn, Seoul 120749, South Korea
[2] Konkuk Univ, Dept Math, Seoul 143701, South Korea
基金
新加坡国家研究基金会;
关键词
Segmentation; Ultrasound images; Rayleigh distribution; Shape constraint; Left ventricle; ENDOCARDIAL BOUNDARY DETECTION; ECHOCARDIOGRAPHIC IMAGES; ACTIVE CONTOURS; ECHO ENVELOPE; B-SCANS; STATISTICS; FRAMEWORK; MODEL;
D O I
10.1016/j.patcog.2012.02.026
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
The segmentation of left ventricle in ultrasound imaging of human heart would provide an important clinical parameter for the evaluation of cardiac functions including volume stroke or ejection fraction and wall motion tracking. We propose a fast segmentation method to reduce laborious manual efforts and conveniently provide robust and stable cardiac quantification to users. The proposed method provides a very simple energy functional form using a predetermined Rayleigh distribution parameter so that the corresponding steepest descent approach with some shape constraints on contour is still capable of fast segmentation. We present several experimental results on two-dimensional echocardiography data for the performance of the proposed model. The experiments show that the proposed model is especially useful when a part of target boundary is seriously corrupted. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3490 / 3500
页数:11
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