Literature DB >> 16398418

Biventricular myocardial strains via nonrigid registration of anatomical NURBS model [corrected].

Nicholas J Tustison1, Amir A Amini.   

Abstract

We present research in which both left and right ventricular deformation is estimated from tagged cardiac magnetic resonance imaging using volumetric deformable models constructed from nonuniform rational B-splines (NURBS). The four model types considered and compared for the left ventricle include two Cartesian NURBS models--one with a cylindrical parameter assignment and one with a prolate spheroidal parameter assignment. The remaining two are non-Cartesian, i.e., prolate spheroidal and cylindrical each with their respective prolate spheroidal and cylindrical parameter assignment regimes. These choices were made based on the typical shape of the left ventricle. For each frame starting with end-diastole, a NURBS model is constructed by fitting two surfaces with the same parameterization to the corresponding set of epicardial and endocardial contours from which a volumetric model is created. Using normal displacements of the three sets of orthogonal tag planes as well as displacements of contour/tag line intersection points and tag plane intersection points, one can solve for the optimal homogeneous coordinates, in a weighted least squares sense, of the control points of the deformed NURBS model at end-diastole using quadratic programming. This allows for subsequent nonrigid registration of the biventricular model at end-diastole to all later time frames. After registration of the model to all later time points, the registered NURBS models are temporally lofted in order to create a comprehensive four-dimensional NURBS model. From the lofted model, we can extract three-dimensional myocardial deformation fields and corresponding Lagrangian and Eulerian strain maps which are local measures of nonrigid deformation. The results show that, in the case of simulated data, the quadratic Cartesian NURBS models with the cylindrical and prolate spheroidal parameter assignments outperform their counterparts in predicting normal strain. The decreased complexity associated with the Cartesian model with the cylindrical parameter assignment prompted its use for subsequent calculations. Lagrangian strains in three canine data, a normal human, and a patient with history of myocardial infarction are presented. Eulerian strains for the normal human data are also included.

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Year:  2006        PMID: 16398418     DOI: 10.1109/TMI.2005.861015

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


  10 in total

1.  Right ventricular strain analysis from three-dimensional echocardiography by using temporally diffeomorphic motion estimation.

Authors:  Zhijun Zhang; Meihua Zhu; Muhammad Ashraf; Craig S Broberg; David J Sahn; Xubo Song
Journal:  Med Phys       Date:  2014-12       Impact factor: 4.071

2.  Regularization-Free Strain Mapping in Three Dimensions, With Application to Cardiac Ultrasound.

Authors:  John J Boyle; Arvin Soepriatna; Frederick Damen; Roger A Rowe; Robert B Pless; Attila Kovacs; Craig J Goergen; Stavros Thomopoulos; Guy M Genin
Journal:  J Biomech Eng       Date:  2019-01-01       Impact factor: 2.097

3.  Internal three-dimensional strains in human intervertebral discs under axial compression quantified noninvasively by magnetic resonance imaging and image registration.

Authors:  Jonathon H Yoder; John M Peloquin; Gang Song; Nick J Tustison; Sung M Moon; Alexander C Wright; Edward J Vresilovic; James C Gee; Dawn M Elliott
Journal:  J Biomech Eng       Date:  2014-11       Impact factor: 2.097

4.  Phase Vector Incompressible Registration Algorithm for Motion Estimation From Tagged Magnetic Resonance Images.

Authors:  Fangxu Xing; Jonghye Woo; Arnold D Gomez; Dzung L Pham; Philip V Bayly; Maureen Stone; Jerry L Prince
Journal:  IEEE Trans Med Imaging       Date:  2017-07-04       Impact factor: 10.048

5.  Three-dimensional plus time biventricular strain from tagged MR images by phase-unwrapped harmonic phase.

Authors:  Bharath Ambale Venkatesh; Chun G Schiros; Himanshu Gupta; Steven G Lloyd; Louis Dell'Italia; Thomas S Denney
Journal:  J Magn Reson Imaging       Date:  2011-07-18       Impact factor: 4.813

6.  N4ITK: improved N3 bias correction.

Authors:  Nicholas J Tustison; Brian B Avants; Philip A Cook; Yuanjie Zheng; Alexander Egan; Paul A Yushkevich; James C Gee
Journal:  IEEE Trans Med Imaging       Date:  2010-04-08       Impact factor: 10.048

7.  Rapid D-Affine biventricular cardiac function with polar prediction.

Authors:  Kathleen Gilbert; Brett R Cowan; Avan Suinesiaputra; Christopher Occleshaw; Alistair A Young
Journal:  Med Image Comput Comput Assist Interv       Date:  2014

8.  Deformable models with sparsity constraints for cardiac motion analysis.

Authors:  Yang Yu; Shaoting Zhang; Kang Li; Dimitris Metaxas; Leon Axel
Journal:  Med Image Anal       Date:  2014-03-27       Impact factor: 8.545

9.  Automated 3D motion tracking using Gabor filter bank, robust point matching, and deformable models.

Authors:  Ting Chen; Xiaoxu Wang; Sohae Chung; Dimitris Metaxas; Leon Axel
Journal:  IEEE Trans Med Imaging       Date:  2009-04-14       Impact factor: 10.048

10.  A graph theoretic approach for computing 3D+time biventricular cardiac strain from tagged MRI data.

Authors:  Ming Li; Himanshu Gupta; Steven G Lloyd; Louis J Dell'Italia; Thomas S Denney
Journal:  Med Image Anal       Date:  2016-06-11       Impact factor: 8.545

  10 in total

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