Publication
MM 2005
Conference paper

Validating cardiac echo diagnosis through video similarity

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Abstract

Video data is increasingly being used in medical diagnosis. Due to the quality of the video and the complexities of underlying motion captured, it is difficult for an in-experienced physician/radiologist to describe motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this paper, we present a method of capturing video similarity and its use for diagnosis verification during decision support. Specifically, we describe the motion information in videos using average velocity curves. Second-order motion statistics are extracted from average velocity curves and serve as features for computing video similarity. Given a new video sample already labeled with a diagnosis, a neighborhood of similar videos is assembled from the training set and their diagnosis labels are used to verify the diagnosis. Copyright © 2005 ACM.

Date

Publication

MM 2005

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