OPTIMIZATION OF MR PULSE SEQUENCES FOR BAYESIAN IMAGE SEGMENTATION

A method for optimizing MR imaging pulse sequence parameters in a stat istical framework is presented. Parameters are defined to be optimal w hen the resulting scalar images yield optimal image segmentations usin g Bayesian pixel classification. Thus, Bayes risk is used as the objec tive function to minimize. Approximations are made to give a tractable solution in a four-step procedure. A sample calculation is carried ou t to determine the optimal TR and flip angle for scalar SPGR imaging o f the brain. Overall, this paper gives a new approach to optimize MRI pulse sequences for the specific objective of improved image segmentat ion.