Realistic analytical polyhedral MRI phantoms

Analytical phantoms have closed form Fourier transform expressions and are used to simulate MRI acquisitions. Existing three‐dimensional (3D) analytical phantoms are unable to accurately model shapes of biomedical interest. The goal of this study was to demonstrate that polyhedral analytical phantoms have closed form Fourier transform expressions and can accurately represent 3D biomedical shapes.

[1]  Alan C. Evans,et al.  An Extensible MRI Simulator for Post-Processing Evaluation , 1996, VBC.

[2]  W. Segars,et al.  4D XCAT phantom for multimodality imaging research. , 2010, Medical physics.

[3]  E. McVeigh,et al.  Three Dimensional Digital Polyhedral Phantom Framework with Analytical Fourier Transform and Application in Cardiac Imaging , 2010 .

[4]  Pierre-Louis Bazin,et al.  Topology-Preserving Tissue Classification of Magnetic Resonance Brain Images , 2007, IEEE Transactions on Medical Imaging.

[5]  Klaas Paul Pruessmann,et al.  Realistic Analytical Phantoms for Parallel Magnetic Resonance Imaging , 2012, IEEE Transactions on Medical Imaging.

[6]  D. Lalush,et al.  A realistic spline-based dynamic heart phantom , 1998, 1998 IEEE Nuclear Science Symposium Conference Record. 1998 IEEE Nuclear Science Symposium and Medical Imaging Conference (Cat. No.98CH36255).

[7]  Benjamin M. W. Tsui,et al.  MCAT to XCAT: The Evolution of 4-D Computerized Phantoms for Imaging Research , 2009, Proceedings of the IEEE.

[8]  R. Irwan,et al.  Fast 3D coronary artery contrast-enhanced magnetic resonance angiography with magnetization transfer contrast, fat suppression and parallel imaging as applied on an anthropomorphic moving heart phantom. , 2006, Magnetic resonance imaging.

[9]  J. Pipe Motion correction with PROPELLER MRI: Application to head motion and free‐breathing cardiac imaging , 1999, Magnetic resonance in medicine.

[10]  John G. Csernansky,et al.  Open Access Series of Imaging Studies (OASIS): Cross-sectional MRI Data in Young, Middle Aged, Nondemented, and Demented Older Adults , 2007, Journal of Cognitive Neuroscience.

[11]  Tao Ju,et al.  Robust repair of polygonal models , 2004, ACM Trans. Graph..

[12]  Shepp La Computerized tomography and nuclear magnetic resonance. , 1980 .

[13]  Evren Özarslan,et al.  Three‐dimensional analytical magnetic resonance imaging phantom in the Fourier domain , 2007, Magnetic resonance in medicine.

[14]  J. Komrska Algebraic expressions of shape amplitudes of polygons and polyhedra , 1988 .

[15]  L. Shepp Computerized Tomography and Nuclear Magnetic Resonance , 1980, Journal of computer assisted tomography.

[16]  Alejandro F Frangi,et al.  Realistic simulation of cardiac magnetic resonance studies modeling anatomical variability, trabeculae, and papillary muscles , 2011, Magnetic resonance in medicine.

[17]  Cynthia B Paschal,et al.  MRI simulator with object-specific field map calculations. , 2004, Magnetic resonance imaging.

[18]  D. Louis Collins,et al.  Design and construction of a realistic digital brain phantom , 1998, IEEE Transactions on Medical Imaging.

[19]  Xiao Han,et al.  CRUISE: Cortical reconstruction using implicit surface evolution , 2004, NeuroImage.

[20]  W. Segars,et al.  MRXCAT: Realistic numerical phantoms for cardiovascular magnetic resonance , 2014, Journal of Cardiovascular Magnetic Resonance.