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Volume of interest‐based fourier transform method for calculation of static magnetic field maps from susceptibility distributions
Author(s) -
Dewal Rahul P.,
Yang Qing X.
Publication year - 2016
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.25747
Subject(s) - computer science , convolution (computer science) , field (mathematics) , algorithm , magnetostatics , volume (thermodynamics) , computer memory , fourier transform , fast fourier transform , magnetic field , artificial intelligence , mathematics , physics , mathematical analysis , computer hardware , semiconductor memory , quantum mechanics , artificial neural network , pure mathematics
Purpose Calculation of static magnetic field (B 0 ) inhomogeneity maps of high‐resolution susceptibility models by means of convolution with dipole kernels often encounters limitations in computer memory (RAM) for large input data matrices. In many applications, only a small portion of the full volume of the computer model is a volume of interest (VOI) or a susceptibility perturbation source. This work presents a VOI‐based method to significantly reduce the computer memory usage for such applications. Theory and Methods The VOI‐based method is presented and compared with the conventional method for calculation of the B 0 field in the brain and heart of a human body model in terms of calculation speed, memory requirement, and calculation error relative to the full model results. Results Use of the VOI‐based method significantly reduced memory usage in the human body model calculations over the conventional method without loss of accuracy and with comparable calculation speed. Conclusion The proposed method can be valuable for rapid calculation of B 0 distributions on standard computer hardware for applications such as subject‐specific B 0 field calculations derived from anatomic scans. Magn Reson Med 75:2473–2480, 2016. © 2015 Wiley Periodicals, Inc.