Fast segmentation of ultrasound images using robust Rayleigh distribution decomposition

Authors:
Chi Young Ahn;Yoon Mo Jung;Oh In Kwon;Jin Keun Seo
Affiliations:
Department of Computational Science and Engineering, Yonsei University, Seoul 120-749, Republic of Korea;Department of Computational Science and Engineering, Yonsei University, Seoul 120-749, Republic of Korea;Department of Mathematics, Konkuk University, Seoul 143-701, Republic of Korea;Department of Computational Science and Engineering, Yonsei University, Seoul 120-749, Republic of Korea
Venue:
Pattern Recognition
Year:
2012

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Abstract

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.