Cardiac motion reconstruction using LKT algorithm from 2D and 3D echocardiography - Details

author：

Gao, A. (Gao, A..) ^[1] | Li, W. (Li, W..) ^[2] | Lin, C. (Lin, C..) ^[3] | Loomes, M. (Loomes, M..) ^[4] | Gao, X. (Gao, X..) ^[5]

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Abstract：

-　The　rhythm　of　the　heart　endows　us　with　not　only　a　life　insurance　but　also　a　barometer　indicating　any　potential　abnormities.　Hence　the　accurate　measurement　of　heart　motion　has　profound　clinical　benefit　in　assisting　diagnostic　decision　making　and　yet　remains　a　challenging　issue　to　be　confronted.　Perceptibly,　heart　motion　can　be　quantified　manually　from　M-mode　diagrams　of　echocardiographs　which　are　created　by　way　of　sound　waves　while　a　patient　undergoing　scanning.　Alternatively,　the　motion　can　be　monitored　automatically　by　post-image　processing　techniques　analyzing　B-mode　video　sequences.　This　paper　explores　the　feasibility　of　the　application　of　Lucas-Kanada-Tomasi　algorithm　towards　the　reconstruction　of　m-mode　diagrams　from　2D　sequences　and　tissue　velocity　curves　from　3D　video　clips　for　the　left　ventricle.　Preliminary　results　reveals　promising　match　between　the　post-processing　findings　and　real-time　scanning　data　and　being　in　consistent　agreement　with　the　similar　studies.　©　2013　CSREA　Press.　All　rights　reserved.

Keyword：

2D and 3D echocardiographs; B-mode; Cardiac motion reconstruction; LKT algorithm; M-mode

Community：

[ 1 ] [Gao, A.]Barts and The London School of Medicine and Dentistry, Queen Mary, University of London, London, E1 2AD, United Kingdom
[ 2 ] [Li, W.]Biomedical Engineering Institute, Fuzhou University, Fuzhou, Fujian, 350002, China
[ 3 ] [Li, W.]School of Science and Technology, Middlesex University, London, NW4 4BT, United Kingdom
[ 4 ] [Lin, C.]Biomedical Engineering Institute, Fuzhou University, Fuzhou, Fujian, 350002, China
[ 5 ] [Loomes, M.]School of Science and Technology, Middlesex University, London, NW4 4BT, United Kingdom
[ 6 ] [Gao, X.]School of Science and Technology, Middlesex University, London, NW4 4BT, United Kingdom

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Source ：

Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013

Year： 2013

Volume： 1

Page： 228-234

Language： English

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