Abstract

A new approach for tracking and quantifying the nonrigid, nonuniform motion of the left ventricular (LV) endocardial wall from cardiac image sequences, on a point-by-point basis over the entire cardiac cycle, is presented. The first step in the algorithm uses one of two approaches to estimate the LV boundary from each image in the sequence. Motion computation involves first matching local segments on one contour to segments on the next contour in the sequence using a shape-based strategy based on bending energy. Results from the match process are incorporated into an optimization functional, along with a smoothness term. The nearest local minimum of the functional to the initial match is found, resulting in a smooth flow field that is consistent with the match data. The computation is performed for all pairs of frames in the temporal sequence and equally sampled points on one contour are tracked throughout the sequence, resulting in a composite flow field over the entire sequence. The method provides a more accurate estimate of perceived motion than previous techniques. >

Keywords:
Tracking (education) Motion (physics) Computer vision Computer science Artificial intelligence

Metrics

22
Cited By
1.71
FWCI (Field Weighted Citation Impact)
29
Refs
0.84
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cardiac Valve Diseases and Treatments
Health Sciences →  Medicine →  Cardiology and Cardiovascular Medicine
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Medical Imaging Techniques and Applications
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging

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