Comparison of perfusion- and diffusion-weighted imaging parameters in brain tumor studies processed using different software platforms.

Rationale And Objectives: To compare quantitative imaging parameter measures from diffusion- and perfusion-weighted imaging magnetic resonance imaging (MRI) sequences in subjects with brain tumors that have been processed with different software platforms.

Materials And Methods: Scans from 20 subjects with primary brain tumors were selected from the Comprehensive Neuro-oncology Data Repository at Washington University School of Medicine (WUSM) and the Swedish Neuroscience Institute. MR images were coregistered, and each subject's data set was processed by three software packages: 1) vendor-specific scanner software, 2) research software developed at WUSM, and 3) a commercially available, Food and Drug Administration-approved, processing platform (Nordic Ice).

The fast automatic algorithm for correction of MR bias field.

Purpose: To develop a method for efficient automatic correction of slow-varying nonuniformity in MR images.

Materials And Methods: The original MR image is represented by a piecewise constant function, and the bias (nonuniformity) field of an MR image is modeled as multiplicative and slow varying, which permits to approximate it with a low-order polynomial basis in a "log-domain." The basis coefficients are determined by comparing partial derivatives of the modeled bias field with the original image.