An improved version of white matter method for correction of non-uniform intensity in MR images: application to the quantification of rates of brain atrophy in Alzheimer's disease and normal aging

A fully automated 3D version of the so-called white matter method for correcting intensity non-uniformity in MR T1-weighted neuro images is presented. The algorithm is an extension of the original work published previously. The major part of the extension was the development of a fully automated method for the generation of the reference points. In the design of this method, a number of measures were introduced to minimize the effects of possible inclusion of non-white matter voxels in the selection process. The correction process has been made iterative. PI drawback of this approach is an increased cost in computational time. The algorithm has been tested on T1-weighted MR images acquired from a longitudinal study involving elderly subjects and people with probable Alzheimer's disease. More quantitative measures were used for the evaluation of the algorithm's performance. Highly satisfactory correction results have been obtained for images with extensive intensity non-uniformity either present in raw data or added artificially. With intensity correction, improved accuracy in the measurement of the rate of brain atrophy in Alzheimer's patients as well as in elderly people due to normal aging has been achieved