Method for Segmentation of the Endocardium and Epicardium of the Left Ventricle in Cardiac Magnetic Resonance Images

Wang, Yuanquan; Jia, Yuheng

doi:10.3724/sp.j.1001.2009.03557

Journal of Software

2010

DOI: 10.3724/sp.j.1001.2009.03557

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Method for Segmentation of the Endocardium and Epicardium of the Left Ventricle in Cardiac Magnetic Resonance Images

Yuanquan Wang¹,

Yuheng Jia²

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2010

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Cited by 1 publication

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Visual speech recognition using Convolutional VEF snake and canonical correlations

Jia

2010

2010 IEEE Youth Conference on Information, Computing and Telecommunications

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This paper presents a novel approach for automatic visual speech recognition using Convolutional VEF snake and canonical correlations. The utterance image sequences of isolated Chinese words are recorded with a headmounted camera, and we use Convolutional VEF snake model to detect and track lip boundary rapidly and accurately. Geometric and motion features are both extracted from lip contour sequences and concatenated to form a joint feature descriptor. Canonical correlation is applied to measure the similarity of two utterance feature matrices and a linear discriminant function is introduced to make further improvement on the recognition accuracy. Experimental results demonstrate that our approach is promising and the joint feature descriptor is more robust than individual ones.

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Visual speech recognition using Convolutional VEF snake and canonical correlations

Jia

2010

2010 IEEE Youth Conference on Information, Computing and Telecommunications

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Method for Segmentation of the Endocardium and Epicardium of the Left Ventricle in Cardiac Magnetic Resonance Images

Cited by 1 publication

References 12 publications

Visual speech recognition using Convolutional VEF snake and canonical correlations

Visual speech recognition using Convolutional VEF snake and canonical correlations

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