Automatic Classification of Intracardiac Tumor and Thrombi in Echocardiography Based on Sparse Representation

作者：Guo Yi^*; Wang Yuanyuan; Kong Dehong; Shu Xianhong

来源：IEEE Journal of Biomedical and Health Informatics, 2015, 19(2): 601-611.

DOI：10.1109/JBHI.2014.2313132

• Automatic classification
• echocardiography
• intracardiac tumor and thrombi
• sparse representation

Identification of intracardiac masses in echocardiograms is one important task in cardiac disease diagnosis. To improve diagnosis accuracy, a novel fully automatic classification method based on the sparse representation is proposed to distinguish intracardiac tumor and thrombi in echocardiography. First, a region of interest is cropped to define the mass area. Then, a unique globally denoising method is employed to remove the speckle and preserve the anatomical structure. Subsequently, the contour of the mass and its connected atrial wall are described by the K-singular value decomposition and a modified active contour model. Finally, the motion, the boundary as well as the texture features are processed by a sparse representation classifier to distinguish two masses. Ninety-seven clinical echocardiogram sequences are collected to assess the effectiveness. Compared with other state-of-the-art classifiers, our proposed method demonstrates the best performance by achieving an accuracy of 96.91%, a sensitivity of 100%, and a specificity of 93.02%. It explicates that our method is capable of classifying intracardiac tumors and thrombi in echocardiography, potentially to assist the cardiologists in the clinical practice.

• 出版日期2015-3
• 单位复旦大学