Literature DB >> 21997253

Cardiac motion and deformation recovery from MRI: a review.

Hui Wang1, Amir A Amini.   

Abstract

Magnetic resonance imaging (MRI) is a highly advanced and sophisticated imaging modality for cardiac motion tracking and analysis, capable of providing 3D analysis of global and regional cardiac function with great accuracy and reproducibility. In the past few years, numerous efforts have been devoted to cardiac motion recovery and deformation analysis from MR image sequences. Many approaches have been proposed for tracking cardiac motion and for computing deformation parameters and mechanical properties of the heart from a variety of cardiac MR imaging techniques. In this paper, an updated and critical review of cardiac motion tracking methods including major references and those proposed in the past ten years is provided. The MR imaging and analysis techniques surveyed are based on cine MRI, tagged MRI, phase contrast MRI, DENSE, and SENC. This paper can serve as a tutorial for new researchers entering the field.

Mesh:

Year:  2011        PMID: 21997253     DOI: 10.1109/TMI.2011.2171706

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


  27 in total

1.  Dictionary-Driven Ischemia Detection From Cardiac Phase-Resolved Myocardial BOLD MRI at Rest.

Authors:  Marco Bevilacqua; Rohan Dharmakumar; Sotirios A Tsaftaris
Journal:  IEEE Trans Med Imaging       Date:  2015-08-19       Impact factor: 10.048

2.  Interpretation of cardiac wall motion from cine-MRI combined with parametric imaging based on the Hilbert transform.

Authors:  Narjes Benameur; Enrico Gianluca Caiani; Younes Arous; Nejmeddine Ben Abdallah; Tarek Kraiem
Journal:  MAGMA       Date:  2017-02-20       Impact factor: 2.310

3.  Spatiotemporal Strategies for Joint Segmentation and Motion Tracking From Cardiac Image Sequences.

Authors:  Huafeng Liu; Ting Wang; Lei Xu; Pengcheng Shi
Journal:  IEEE J Transl Eng Health Med       Date:  2017-02-23       Impact factor: 3.316

Review 4.  Generating anatomical models of the heart and the aorta from medical images for personalized physiological simulations.

Authors:  J Weese; A Groth; H Nickisch; H Barschdorf; F M Weber; J Velut; M Castro; C Toumoulin; J L Coatrieux; M De Craene; G Piella; C Tobón-Gomez; A F Frangi; D C Barber; I Valverde; Y Shi; C Staicu; A Brown; P Beerbaum; D R Hose
Journal:  Med Biol Eng Comput       Date:  2013-01-30       Impact factor: 2.602

5.  Combined identification of septal flash and absence of myocardial scar by cardiac magnetic resonance imaging improves prediction of response to cardiac resynchronization therapy.

Authors:  Manav Sohal; Sana Amraoui; Zhong Chen; Eva Sammut; Tom Jackson; Matthew Wright; Mark O'Neill; Jaswinder Gill; Gerald Carr-White; C Aldo Rinaldi; Reza Razavi
Journal:  J Interv Card Electrophysiol       Date:  2014-06-12       Impact factor: 1.900

6.  A Meshfree Representation for Cardiac Medical Image Computing.

Authors:  Heye Zhang; Zhifan Gao; Lin Xu; Xingjian Yu; Ken C L Wong; Huafeng Liu; Ling Zhuang; Pengcheng Shi
Journal:  IEEE J Transl Eng Health Med       Date:  2018-01-18       Impact factor: 3.316

7.  Automated contour tracking and trajectory classification of pelvic organs on dynamic MRI.

Authors:  Iman Nekooeimehr; Susana Lai-Yuen; Paul Bao; Alfredo Weitzenfeld; Stuart Hart
Journal:  J Med Imaging (Bellingham)       Date:  2018-03-30

8.  Regional dynamics of fractal dimension of the left ventricular endocardium from cine computed tomography images.

Authors:  Ashish Manohar; Lorenzo Rossini; Gabrielle Colvert; Davis M Vigneault; Francisco Contijoch; Marcus Y Chen; Juan C Del Alamo; Elliot R McVeigh
Journal:  J Med Imaging (Bellingham)       Date:  2019-11-08

9.  Estimating Aggregate Cardiomyocyte Strain Using In Vivo Diffusion and Displacement Encoded MRI.

Authors:  Ilya A Verzhbinsky; Luigi E Perotti; Kevin Moulin; Tyler E Cork; Michael Loecher; Daniel B Ennis
Journal:  IEEE Trans Med Imaging       Date:  2019-08-08       Impact factor: 10.048

10.  A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters.

Authors:  Hong Liu; Jie Wang; Xiangyang Xu; Enmin Song; Qian Wang; Renchao Jin; Chih-Cheng Hung; Baowei Fei
Journal:  Magn Reson Imaging       Date:  2014-08-01       Impact factor: 2.546

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