Literature DB >> 12374316

Estimation of 3-D left ventricular deformation from medical images using biomechanical models.

Xenophon Papademetris1, Albert J Sinusas, Donald P Dione, R Todd Constable, James S Duncan.   

Abstract

The quantitative estimation of regional cardiac deformation from three-dimensional (3-D) image sequences has important clinical implications for the assessment of viability in the heart wall. We present here a generic methodology for estimating soft tissue deformation which integrates image-derived information with biomechanical models, and apply it to the problem of cardiac deformation estimation. The method is image modality independent. The images are segmented interactively and then initial correspondence is established using a shape-tracking approach. A dense motion field is then estimated using a transversely isotropic, linear-elastic model, which accounts for the muscle fiber directions in the left ventricle. The dense motion field is in turn used to calculate the deformation of the heart wall in terms of strain in cardiac specific directions. The strains obtained using this approach in open-chest dogs before and after coronary occlusion, exhibit a high correlation with strains produced in the same animals using implanted markers. Further, they show good agreement with previously published results in the literature. This proposed method provides quantitative regional 3-D estimates of heart deformation.

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Year:  2002        PMID: 12374316     DOI: 10.1109/TMI.2002.801163

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  30 in total

1.  Incompressible deformation estimation algorithm (IDEA) from tagged MR images.

Authors:  Xiaofeng Liu; Khaled Z Abd-Elmoniem; Maureen Stone; Emi Z Murano; Jiachen Zhuo; Rao P Gullapalli; Jerry L Prince
Journal:  IEEE Trans Med Imaging       Date:  2011-09-19       Impact factor: 10.048

2.  Fast plaque burden assessment of the femoral artery using 3D black-blood MRI and automated segmentation.

Authors:  Bernard Chiu; Jie Sun; Xihai Zhao; Jinnan Wang; Niranjan Balu; Jiachang Chi; Jianrong Xu; Chun Yuan; William S Kerwin
Journal:  Med Phys       Date:  2011-10       Impact factor: 4.071

3.  Bidirectional segmentation of three-dimensional cardiac MR images using a subject-specific dynamical model.

Authors:  Yun Zhu; Xenophon Papademetris; Albert J Sinusas; James S Duncan
Journal:  Med Image Comput Comput Assist Interv       Date:  2008

Review 4.  Deformable medical image registration: a survey.

Authors:  Aristeidis Sotiras; Christos Davatzikos; Nikos Paragios
Journal:  IEEE Trans Med Imaging       Date:  2013-05-31       Impact factor: 10.048

5.  Segmentation of Left Ventricle From 3D Cardiac MR Image Sequences Using A Subject-Specific Dynamical Model.

Authors:  Yun Zhu; Xenophon Papademetris; Albert Sinusas; James S Duncan
Journal:  Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit       Date:  2008

6.  Brain Shape Characterization from Deformation.

Authors:  Lawrence H Staib; Marcel Jackowski; Xenophon Papademetris
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2006

7.  Flow network tracking for spatiotemporal and periodic point matching: Applied to cardiac motion analysis.

Authors:  Nripesh Parajuli; Allen Lu; Kevinminh Ta; John Stendahl; Nabil Boutagy; Imran Alkhalil; Melissa Eberle; Geng-Shi Jeng; Maria Zontak; Matthew O'Donnell; Albert J Sinusas; James S Duncan
Journal:  Med Image Anal       Date:  2019-04-18       Impact factor: 8.545

8.  A Dynamical Shape Prior for LV Segmentation from RT3D Echocardiography.

Authors:  Yun Zhu; Xenophon Papademetris; Albert J Sinusas; James S Duncan
Journal:  Med Image Comput Comput Assist Interv       Date:  2009

9.  Segmentation of the left ventricle from cardiac MR images using a subject-specific dynamical model.

Authors:  Yun Zhu; Xenophon Papademetris; Albert J Sinusas; James S Duncan
Journal:  IEEE Trans Med Imaging       Date:  2009-09-29       Impact factor: 10.048

10.  Non-rigid registration of breast surfaces using the laplace and diffusion equations.

Authors:  Rowena E Ong; Jao J Ou; Michael I Miga
Journal:  Biomed Eng Online       Date:  2010-02-12       Impact factor: 2.819

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