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Wall motion classification of stress echocardiography based on combined rest-and-stress data.

Abstract:

In this paper, we represent a new framework that performs automated local wall motion analysis based on the combined information derived from a rest and stress sequence (a full stress echocardiography study). Since cardiac data inherits time-varying and sequential properties, we introduce a Hidden Markov Model (HMM) approach to classify stress echocardiography. A wall segment model is developed for a normal and an abnormal heart and experiments are performed on rest, stress and rest-and-stres...

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Publication status:
Published

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Journal:
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Volume:
11
Issue:
Pt 2
Pages:
139-146
Publication date:
2008-01-01
ISSN:
0302-9743
Source identifiers:
62576

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