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3D Point Wise Tracking of the Left Ventricle Over Cardiac Image Sequences Using Active Mesh and Physical Models Publisher



Kermasni S1 ; Moradi MH1 ; Abrishamimoghaddam H2 ; Saneei H3 ; Marashishoshtari MJ4
Authors
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Authors Affiliations
  1. 1. Department of Bioelectronics, Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran 15875-4413, 424 Hafez Ave., Iran
  2. 2. Department of Electrical Engineering, K. N. Toosi University of Technology, Tehran 16315-1355, Iran
  3. 3. Department of Internal Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
  4. 4. Department of Radiology, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Journal of Applied Sciences Published:2008


Abstract

This study presents a strategy for point wise tracking of the Left Ventricle (LV) and recovering its motion field by 3D Active Mesh Model (AMM) and also continuum mechanics over 3D anatomical cine cardiac magnetic resonance imaging. The method is developed in the framework of the on-going work on application of mathematical modeling to image sequence analysis of cardiac wall as a non-rigid object. The model is composed of topology and geometry of LV and associated elastic material properties. The initial model acquires its knowledge directly from the 3D images in end diastolic phase. The LV deformation is estimated by fitting the model to the initial sparse displacement which is measured from a new establishing point correspondence procedure. The proposed approach is capable of estimating the displacement field for every desired points of myocardial wall, then it leads to measure dense motion field and local dynamic parameters such as Lagrangian strain. In this study, eight image sequences (including six real and two synthetic sets) were used and findings were in good agreement with those reported by other researchers. For synthetic image sequence sets, the mean square error between length of motion field estimated by the algorithm and analytical values was less than 1 mm. The results demonstrated the superiority of the novel strategy with respect to formerly presented algorithm mentioned in this study. This algorithm is more accurate while the running time has been reduced to one third. Furthermore, the results are comparable to the current state-of-the-art methods. © 2008 Asian Network for Scientific Information.