Atherosclerotic plaque motion analysis from ultrasound videos

S. E. Murillo; M. S. Pattichis; C. P. Loizou; C. S. Pattichis; E. Kyriacou; A. G. Constantinides; A. Nicolaides

doi:10.1109/ACSSC.2006.354867

Atherosclerotic plaque motion analysis from ultrasound videos

S. E. Murillo, M. S. Pattichis, C. P. Loizou, C. S. Pattichis, E. Kyriacou, A. G. Constantinides, A. Nicolaides

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, we describe a collection of algorithms that are used to provide motion trajectory estimates from atherosclerotic plaque ultrasound videos. Our approach is based on the use of four different optical flow methods to estimate motion vectors (Horn and Schunk, Lucas, Nagel and Uras). To estimate the optimal motion estimation parameters, we perform hundreds of experiments on a Linux cluster, and further validate the results using synthetic simulations. Following motion estimation, we compute pixel motion trajectories over the plaque regions and vessel walls. Pixel trajectories are then used to assess plaque deformation.

Original language	English
Title of host publication	Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06
Pages	836-840
Number of pages	5
DOIs	https://doi.org/10.1109/ACSSC.2006.354867
Publication status	Published - 2006
Event	40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 - Pacific Grove, CA, United States Duration: 29 Oct 2006 → 1 Nov 2006

Other

Other	40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06
Country/Territory	United States
City	Pacific Grove, CA
Period	29/10/06 → 1/11/06

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10.1109/ACSSC.2006.354867

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@inproceedings{92347d965a544327bfada64a3317eab2,

title = "Atherosclerotic plaque motion analysis from ultrasound videos",

abstract = "In this paper, we describe a collection of algorithms that are used to provide motion trajectory estimates from atherosclerotic plaque ultrasound videos. Our approach is based on the use of four different optical flow methods to estimate motion vectors (Horn and Schunk, Lucas, Nagel and Uras). To estimate the optimal motion estimation parameters, we perform hundreds of experiments on a Linux cluster, and further validate the results using synthetic simulations. Following motion estimation, we compute pixel motion trajectories over the plaque regions and vessel walls. Pixel trajectories are then used to assess plaque deformation.",

author = "Murillo, {S. E.} and Pattichis, {M. S.} and Loizou, {C. P.} and Pattichis, {C. S.} and E. Kyriacou and Constantinides, {A. G.} and A. Nicolaides",

year = "2006",

doi = "10.1109/ACSSC.2006.354867",

language = "English",

isbn = "1424407850",

pages = "836--840",

booktitle = "Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06",

note = "40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 ; Conference date: 29-10-2006 Through 01-11-2006",

}

Murillo, SE, Pattichis, MS, Loizou, CP, Pattichis, CS, Kyriacou, E, Constantinides, AG & Nicolaides, A 2006, Atherosclerotic plaque motion analysis from ultrasound videos. in Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06., 4176677, pp. 836-840, 40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06, Pacific Grove, CA, United States, 29/10/06. https://doi.org/10.1109/ACSSC.2006.354867

TY - GEN

T1 - Atherosclerotic plaque motion analysis from ultrasound videos

AU - Murillo, S. E.

AU - Pattichis, M. S.

AU - Loizou, C. P.

AU - Pattichis, C. S.

AU - Kyriacou, E.

AU - Constantinides, A. G.

AU - Nicolaides, A.

PY - 2006

Y1 - 2006

N2 - In this paper, we describe a collection of algorithms that are used to provide motion trajectory estimates from atherosclerotic plaque ultrasound videos. Our approach is based on the use of four different optical flow methods to estimate motion vectors (Horn and Schunk, Lucas, Nagel and Uras). To estimate the optimal motion estimation parameters, we perform hundreds of experiments on a Linux cluster, and further validate the results using synthetic simulations. Following motion estimation, we compute pixel motion trajectories over the plaque regions and vessel walls. Pixel trajectories are then used to assess plaque deformation.

AB - In this paper, we describe a collection of algorithms that are used to provide motion trajectory estimates from atherosclerotic plaque ultrasound videos. Our approach is based on the use of four different optical flow methods to estimate motion vectors (Horn and Schunk, Lucas, Nagel and Uras). To estimate the optimal motion estimation parameters, we perform hundreds of experiments on a Linux cluster, and further validate the results using synthetic simulations. Following motion estimation, we compute pixel motion trajectories over the plaque regions and vessel walls. Pixel trajectories are then used to assess plaque deformation.

UR - http://www.scopus.com/inward/record.url?scp=47049085331&partnerID=8YFLogxK

U2 - 10.1109/ACSSC.2006.354867

DO - 10.1109/ACSSC.2006.354867

M3 - Conference contribution

AN - SCOPUS:47049085331

SN - 1424407850

SN - 9781424407859

SP - 836

EP - 840

BT - Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06

T2 - 40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06

Y2 - 29 October 2006 through 1 November 2006

ER -

Atherosclerotic plaque motion analysis from ultrasound videos

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