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Abstract #2805

Accurate Simulation of Signal and Noise in MRI Based on Electromagnetic Field Calculation and Bloch Simulation

Zhipeng Cao1, Christopher T. Sica2, Wei Luo2, Sukhoon Oh3, Christopher Michael Collins3

1Radiology, Pennsylvania State University, Hershey, PA, United States; 2Radiology, The Pennsylvania State University, Hershey, PA, United States; 3Radiology, New York University, New York City, NY, United States

A method for generating simulated MR images (starting with knowledge of only pulse sequence, receiver bandwidth, and distributions of sample properties and field distributions through space) with realistic levels of noise is described and demonstrated with comparison to experimentally-measured SNR.

Keywords

accuracy accurate accurately actual although anatomical applied array asymmetries bandwidth birdcage calculation chain channel city classic close coil commercially complete complex conductivity constant control correct correlated created cylindrical deduced density detailed development deviation diagonal digital discrepancies distilled distribution distributions dividing easily effective electric electromagnetic element elements ensure equilibrium equivalent event evolution expected experiment experimental experimentally explained expression extended extremity field fields finally funding generate generating generation goal gradient helps identical incorporate increasingly input inputs inside interference interplayed listed local magnetization magnitude mapping matched matrix measured model models multichannel noise noted numerical pattern perfect perfectly phantom plank probe proposed pulse quality radiology random real realistic receive receiver recent recovery rectangular reflecting related required requires resistance resolution sample scaled scaling scanned scanner selective separate series setup simulated simulation simulator since slight slightly software solvers spoiling steps system temperature theory throughout tissue towards transmit unit utility utilizing validate validated validation variance vector vectors years