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PubMed · 16224844

Automatic segmentation of echocardiography based on a morphological reconstruction algorithm.

Xian-hua Shen·De-yu Li·Jiang-li Lin·Tian-fu Wang·Xiao-hui Wen·Chang-qiong Zheng·Li Rao·Hong Tang
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Abstract

OBJECTIVE: To improve the precision of the traditional segmentation of echocardiogram, by suppressing the influence from inherent speckle noises in medical ultrasonic images. METHOD: An automatic segmentation method based on reconstructed morphology was proposed in this paper. First, the opening and closing operations by reconstruction were imposed to the ultrasonic image. Second, the top-hat operation was used to extract the bright and/or dark features and to find out the boundaries corresponding to these features, whereby implemented the automatic segmentation. RESULT: The segmented echocardiogram had less artificial boundaries resulted from speckle noise, and could accurately be extracted the artery and ventricle. CONCLUSION: The presented method can detect both dark and bright objects accurately, and the boundary has a fine continuity. In addition, the algorithm is also applicable to the extraction of sole bright/dark features, accordingly to reduce the complexity and time needed and to improve the accuracy.

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AlgorithmsAnimalsArtifactsCardiovascular Physiological PhenomenaDogsEchocardiographyHumansImage Processing, Computer-AssistedSwineJournal ArticleResearch Support, Non-U.S. Gov't

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Xian-hua Shen, De-yu Li, Jiang-li Lin, Tian-fu Wang, Xiao-hui Wen, Chang-qiong Zheng, Li Rao, Hong Tang. 2005. Automatic segmentation of echocardiography based on a morphological reconstruction algorithm.. https://pubmed.ncbi.nlm.nih.gov/16224844/

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