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Robust boundary detection of left ventricles on ultrasound images using ASM-level set method

Issue title: Frontiers in Biomedical Engineering and Biotechnology – Proceedings of the 4th International Conference on Biomedical Engineering and Biotechnology, 18–21 August 2015, Shanghai, China

Guest editors: Feng Liu, Dong-Hoon Lee, Ricardo Lagoa and Sandeep Kumar

Article type: Research Article

Authors: Zhang, Yaonan; * | Gao, Yuan | Li, Hong | Teng, Yueyang | Kang, Yan

Affiliations: Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, China

Correspondence: [*] Address for correspondence: Yaonan Zhang, Sino-Dutch Biomedical and Information Engineering School, Northeastern University (Hunnan Campus), P.O. Box H004, 500 Zhihui Dajie, Hunnan District, Shenyang, China. Tel.: +86-24-83685261; Fax: +86-24-83681955; E-mail: [email protected].

Keywords: Level set method, image segmentation, active shape model

DOI: 10.3233/BME-151427

Journal: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1291-S1296, 2015

Published: 2015
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Level set method has been widely used in medical image analysis, but it has difficulties when being used in the segmentation of left ventricular (LV) boundaries on echocardiography images because the boundaries are not very distinguish, and the signal-to-noise ratio of echocardiography images is not very high. In this paper, we introduce the Active Shape Model (ASM) into the traditional level set method to enforce shape constraints. It improves the accuracy of boundary detection and makes the evolution more efficient. The experiments conducted on the real cardiac ultrasound image sequences show a positive and promising result.

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