Paper
12 March 2010 Global optimization for motion estimation with applications to ultrasound videos of carotid artery plaques
Sergio Murillo, Marios Pattichis, Peter Soliz, Simon Barriga, C. P. Loizou, C. S. Pattichis
Author Affiliations +
Abstract
Motion estimation from digital video is an ill-posed problem that requires a regularization approach. Regularization introduces a smoothness constraint that can reduce the resolution of the velocity estimates. The problem is further complicated for ultrasound videos (US), where speckle noise levels can be significant. Motion estimation using optical flow models requires the modification of several parameters to satisfy the optical flow constraint as well as the level of imposed smoothness. Furthermore, except in simulations or mostly unrealistic cases, there is no ground truth to use for validating the velocity estimates. This problem is present in all real video sequences that are used as input to motion estimation algorithms. It is also an open problem in biomedical applications like motion analysis of US of carotid artery (CA) plaques. In this paper, we study the problem of obtaining reliable ultrasound video motion estimates for atherosclerotic plaques for use in clinical diagnosis. A global optimization framework for motion parameter optimization is presented. This framework uses actual carotid artery motions to provide optimal parameter values for a variety of motions and is tested on ten different US videos using two different motion estimation techniques.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sergio Murillo, Marios Pattichis, Peter Soliz, Simon Barriga, C. P. Loizou, and C. S. Pattichis "Global optimization for motion estimation with applications to ultrasound videos of carotid artery plaques", Proc. SPIE 7629, Medical Imaging 2010: Ultrasonic Imaging, Tomography, and Therapy, 76290X (12 March 2010); https://doi.org/10.1117/12.844496
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Cited by 2 scholarly publications.
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KEYWORDS
Video

Motion estimation

Ultrasonography

Arteries

Motion models

Optical flow

Speckle

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