Generation of Realistic 4D Synthetic CSPAMM Tagged MR Sequences for Benchmarking Cardiac Motion Tracking Algorithms

2016 ◽  
pp. 108-117 ◽  
Author(s):  
Yitian Zhou ◽  
Mathieu De Craene ◽  
Oudom Somphone ◽  
Maxime Sermesant ◽  
Olivier Bernard
Keyword(s):  
Motion Tracking ◽  
Cardiac Motion ◽  
Tracking Algorithms ◽  
Mr Sequences

Towards Benchmarking of Video Motion Tracking Algorithms

2010 ◽  
Author(s):  
Mukesh Motwani ◽  
Nishith Tirpankar ◽  
Rakhi Motwani ◽  
Monica Nicolescu ◽  
Frederick C. Harris Jr.
Keyword(s):  
Motion Tracking ◽  
Tracking Algorithms

Spline-Based Cardiac Motion Tracking Using Velocity-Encoded Magnetic Resonance Imaging

2008 ◽  
Vol 27 (8) ◽  
pp. 1045-1053 ◽  
Author(s):  
E. Bergvall ◽  
E. Hedstrom ◽  
K.M. Bloch ◽  
H. Arheden ◽  
G. Sparr
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Motion Tracking ◽  
Cardiac Motion ◽  
Resonance Imaging

Non-Rigid Image Registration based on Parameterized Surfaces: Application to 3D Cardiac Motion Image Analysis

2021 ◽  
pp. 2250028
Author(s):  
Said Khalid Shah
Keyword(s):  
Image Registration ◽  
Motion Tracking ◽  
Salient Feature ◽  
Ct Images ◽  
Heart Beat ◽  
Cardiac Motion ◽  
Free Form ◽  
3D Ct ◽  
Registration Accuracy ◽  
Whole Heart

This paper describes the Fast Radial Basis Function (RBF) method for cardiac motion tracking in 3D CT using non-rigid medical image registration based on parameterized (regular) surfaces. The technique is a point-based registration evaluation algorithm which does register 3D MR or CT images in real time. We first extract the surface of the whole heart 3D CT and its contrast enhanced part (left ventricle (LV) blood cavity) of each dataset with a semiautomatic contouring and a fully-automatic triangulation method followed by a global surface parameterization and optimization algorithm. In second step, a set of registration experiments are run to calculate the deformation field at various phases of cardiac motion or cycle from CT images, which results into significant deformation during each phase of a cycle. The surface points of the whole heart and LV are used to register the source systole image to various diastole target images taken at different phases during a heart beat. Our registration accuracy improves with the increase in number of salient feature points (i.e. optimized parameterized surfaces) and it has no effect on the speed of the algorithm (i.e. still less than a second). The results show that the target registration error is less than 3[Formula: see text]mm (2.53) and the performance of the Fast RBF algorithm is less than a second using a whole heart CT dataset of a single patient taken over the course of the entire cardiac cycle. At the end, the results for recovery (or analysis) of bigger deformation in heart CT images using the Fast RBF algorithm is compared to the state-of-the-art Free Form Deformation (FFD) registration technique. It is proved that the Fast RBF method is performing better in speed and slightly less accurate than the FFD (when measured in terms of NMI) due to iterative nature of the latter.

scholarly journals Cardiac motion tracking using CINE harmonic phase (HARP) magnetic resonance imaging

1999 ◽  
Vol 42 (6) ◽  
pp. 1048-1060 ◽  
Author(s):  
Nael F. Osman ◽  
William S. Kerwin ◽  
Elliot R. McVeigh ◽  
Jerry L. Prince
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Motion Tracking ◽  
Cardiac Motion ◽  
Resonance Imaging ◽  
Harmonic Phase

Correction to "Spline-Based Cardiac Motion Tracking Using Velocity-Encoded Magnetic Resonance Imaging"

2011 ◽  
Vol 30 (1) ◽  
pp. 169-169
Author(s):  
Erik Bergvall ◽  
Erik Hedström ◽  
Karin Markenroth Bloch ◽  
Håkan Arheden ◽  
Gunnar Sparr
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Motion Tracking ◽  
Cardiac Motion ◽  
Resonance Imaging
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