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Introduction of automated methods for heart function assessment have the potential to minimize the variance in operator assessment. This paper considers automated classification of rest and stress echocardiography. One previous attempt has been made to combine information from rest and stress sequences utilizing a Hidden Markov Model (HMM), which has proven to be the best performing approach to date...
In stress echocardiography, the heart is imaged at rest and again when stressed to observe the change in function between these two states; the idea being that abnormalities will be exaggerated and therefore easier to identify in stress, but importantly this is referenced to the rest state. Despite the development of segmentation and tracking techniques for the heart at rest, there is little literature...
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