RELIABILITY AND VALIDITY OF AN ALGORITHM FOR FUZZY TISSUE SEGMENTATION OF MRI

Purpose: A new multistep, volumetric-based tissue segmentation algorit hm that results in fuzzy (or probabilistic) voxel description is descr ibed. This algorithm is designed to accurately segment gray matter, wh ite matter, and CSF and can be applied to both single channel high res olution and multispectral (multiecho) MR images. Method: The reliabili ty and validity of this method are evaluated by assessing (a) the stab ility of the algorithm across time, rater, and pulse sequence; (b) the accuracy of the method when applied to both real and synthetic image datasets; and (c) differences in specific tissue volumes between indiv iduals with a specific genetic condition (fragile X syndrome) and norm al control subjects. Results: The algorithm was found to have high rel iability, accuracy, and validity. The finding of increased caudate gra y matter volume associated with the fragile X syndrome is replicated i n this sample. Conclusion: Since this segmentation approach incorporat es ''fuzzy'' or probabilistic methods, it has the potential to more ac curately address partial volume effects, anatomical variation within ' 'pure'' tissue compartments, and more subtle changes in tissue volumes as a result of disease and treatment. The method is a component of so ftware that is available in the public domain and has been implemented on an inexpensive personal computer, thus offering an attractive and promising method for determining the status and progression of both no rmal development and pathology of the CNS.