Automatic apical view classification of echocardiograms using a discriminative learning dictionary

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• 作者：Hanan Khamis^a ; ¹ ; ^{khamishanan@gmail.com} ; Grigoriy Zurakhov^a ; ¹ ; Vered Azar^a ; Adi Raz^a ; Zvi Friedman^b ; Dan Adam^a
• 关键词：Echocardiography ; Echocardiogram classification ; Cuboid-detector ; Supervised dictionary learning ; LC-KSVD
• 刊名：Medical Image Analysis
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：36
• 期：Complete
• 页码：15-21
• 全文大小：1156 K
• 卷排序：36

文摘

Automatic classification of the three standard apical views (A4C, A2C and ALX) is essential for the automation of cardiac functional assessment. A multi-stage algorithm for the classification of the apical echocardiogram views is presented. The algorithm employs spatio-temporal feature extraction and supervised dictionary learning approaches to uniquely enhance the classification accuracies of the echocardiograms. A total classification accuracy of 95% is reported with a feasibility to real-time implementation.