Echocardiogram View Classification using Edge Filtered Scale-invariant Motion Features

In an 2D echocardiogram exam, an ultrasound probe samples the heart with 2D slices. Changing the orientation and position on the probe changes the slice viewpoint, altering the cardiac anatomy being imaged. The determination of the probe viewpoint forms an essential step in automatic cardiac echo image analysis. In this paper we present a system for automatic view classification that exploits cues from both cardiac structure and motion in echocardiogram videos. In our framework, each image from the echocardiogram video is represented by a set of novel salient features. We locate these features at scale invariant points in the edge-filtered motion magnitude images and encode them using local spatial, textural and kinetic information. Training in our system involves learning a hierarchical feature dictionary and parameters of a Pyramid Matching Kernel based Support Vector Machine. While testing, each image, classified independently, casts a votes towards parent video cla...

• Type: Conference
• Year: 2009
• Where: CVPR
• Authors: Ritwik Kumar, Fei Wang, David Beymer, Tanveer Fathima Syeda-Mahmood
• Keywords: Computer Vision, CVPR 2009, Echocardiogram Classification, Scale-invariant Motion Features