Finite radial reconstruction for magnetic resonance imaging: a theoretical study

Chandra, Shekhar S., Archchige, Ramitha, Ruben, Gary, Jin, Jin, Li, Mingyan, Kingston, Andrew M., Svalbe, Imants and Crozier, Stuart (2016). Finite radial reconstruction for magnetic resonance imaging: a theoretical study. In: 2015 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2015. International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016, Gold Coast, QLD, Australia, (). 30 November-2 December 2016. doi:10.1109/DICTA.2016.7797043


Author Chandra, Shekhar S.
Archchige, Ramitha
Ruben, Gary
Jin, Jin
Li, Mingyan
Kingston, Andrew M.
Svalbe, Imants
Crozier, Stuart
Title of paper Finite radial reconstruction for magnetic resonance imaging: a theoretical study
Conference name International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016
Conference location Gold Coast, QLD, Australia
Conference dates 30 November-2 December 2016
Convener IEEE
Proceedings title 2015 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2015
Journal name 2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016
Place of Publication Piscataway, NJ, United States
Publisher Institute of Electrical and Electronics Engineers
Publication Year 2016
Sub-type Fully published paper
DOI 10.1109/DICTA.2016.7797043
ISBN 9781509028962
Total pages 6
Language eng
Formatted Abstract/Summary
Magnetic resonance (MR) imaging is an important imaging modality for diagnostic medicine due to its ability to visualize the soft tissue of the human body in three dimensions (3D) without ionizing radiation. MR imaging however, typically relies on measurement techniques that do not exploit the geometry of discrete Fourier space, so called k-space, where the measurements are made. In this work, we firstly present a novel k-space tiling scheme that utilizes the finite geometry of discrete Fourier space via the discrete Fourier slice theorem. This produces a sampling of k-space that is pseudo-radial, to be more noise and patient-movement tolerant, and pseudo-random, further improving robustness to noise, whilst sampling with sufficient density near the central k-space region, where the majority of power of anatomical images lies. Secondly, we introduce a stable and iterative discrete reconstruction scheme for recovering images from their limited k-space measurements (in the form discrete slices) based on the maximum likelihood expectation maximization approach. We study the performance of the proposed approach using simulated MR measurements in k-space.
Keyword MLEM
MRI
Image reconstruction
Fourier slice theorem
Finite Radon transform
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes http://ieeexplore.ieee.org/abstract/document/7797043/

 
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Created: Fri, 20 Jan 2017, 01:27:38 EST by Shekhar Chandra on behalf of School of Information Technol and Elec Engineering