NDLI: Fully automated endocardial contour detection in time sequences of echocardiograms by active appearance motion models

Content Provider	IEEE Xplore Digital Library
Author	Bosch, J.G. Mitchell, S.C. Lelieveldt, B.P.F. Nijland, F. Kamp, O. Sonka, M. Reiber, J.H.C.
Copyright Year	2001
Description	Author affiliation: Med. Center, Leiden Univ., Netherlands (Bosch, J.G.)
Abstract	A novel fully automated border detection technique for phase-normalized echocardiographic image sequences is developed: Active Appearance-Motion Models (AAMM). AAMM finds shape and appearance eigenvariations of the heart over the full cardiac cycle from a set of examples, capturing typical motion patterns. AAMM segments sequences by adjusting eigenvariation coefficients to minimize model-to-target differences. This results in a time-continuous segmentation. The method was applied on 4-chamber sequences from 129 unselected patients, split randomly into training (TRN, n=65) and test set (TST, n=64). In all sequences, an independent expert manually drew endocardial contours (MAN). On TST, fully automated AAMM succeeded in 97% of cases (AUTO) and performed well (average contour distance 3.3 mm, area regression AUTO=0.91 *MAN+1.7 cm/sup 2/, r=0.87). Results outperformed single-frame AAM segmentation and human interobserver variabilities.
Starting Page	93
Ending Page	96
File Size	420218
Page Count	4
File Format	PDF
ISBN	0780372662
ISSN	02766547
DOI	10.1109/CIC.2001.977599
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-09-23
Publisher Place	Netherlands
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Active appearance model Image sequences Image segmentation Principal component analysis Biomedical imaging Motion detection Motion analysis Coherence Cardiology
Content Type	Text
Resource Type	Article

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