Title :
Shear modulus estimation using parallelized partial volumetric reconstruction
Author :
Doyley, Marvin M. ; Van Houten, Elijah E. ; Weaver, John B. ; Poplack, Steven ; Duncan, Laura ; Kennedy, Francis ; Paulsen, Keith D.
Author_Institution :
Dept. of Radiol., Dartmouth-Hitchcock Med. Center, Lebanon, NH, USA
Abstract :
Magnetic resonance elastography can be limited by the computationally intensive nonlinear inversion schemes that are sometimes employed to estimate shear modulus from externally induced internal tissue displacements. Consequently, we have developed a parallelized partial volume reconstruction approach to overcome this limitation. In this paper, we report results from experiments conducted on breast phantoms and human volunteers to validate the proposed technique. More specifically, we demonstrate that computational cost is linearly related to the number of subzones used during image recovery and that both subzone parallelization and partial volume domain reduction decrease execution time accordingly. Importantly, elastograms computed based on the parallelized partial volume technique are not degraded in terms of either image quality or accuracy relative to their full volume counterparts provided that the estimation domain is sufficiently large to negate the effects of boundary conditions. The clinical results presented in this paper are clearly preliminary; however, the parallelized partial volume reconstruction approach performs sufficiently well to warrant more in-depth clinical evaluation.
Keywords :
biological organs; biological tissues; biomechanics; biomedical MRI; image reconstruction; medical image processing; shear modulus; breast phantoms; computationally intensive nonlinear inversion schemes; externally induced internal tissue displacements; image recovery; magnetic resonance elastography; parallelized partial volumetric reconstruction; shear modulus; subzone parallelization; Boundary conditions; Breast; Computational efficiency; Concurrent computing; Degradation; Humans; Image quality; Image reconstruction; Imaging phantoms; Magnetic resonance; Breast cancer detection; elasticity imaging; elastography; inverse elasticity problem; magnetic resonance imaging; parallel computing; shear modulus estimation; Breast Neoplasms; Computing Methodologies; Elasticity; Humans; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Phantoms, Imaging; Reproducibility of Results; Sensitivity and Specificity; Shear Strength;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2004.834624