KEYWORDS: Data modeling, Signal to noise ratio, Magnetic resonance imaging, Model-based design, Tumor growth modeling, Tissues, Tumors, Breast, Fourier transforms, 3D modeling
This paper describes a method for estimating, from dynamic contrast-enhanced MRI raw k-space data of the breast,
parameter maps that model tissue properties associated with a compartmental model of contrast exchange. The contrast
agent kinetics, as represented by these parameter maps, are important in distinguishing benign and malignant tumors.
The proposed model-based reconstruction algorithm estimates tissue parameter maps directly from MRI k-space data,
thereby allowing a new and improved set of spatiotemporal resolution and noise tradeoffs. Realistic noise levels and an
undersampling factor of R=4 appeared to provide reasonable accuracy for the kinetic parameters of interest.
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