Brain tissue classification in MR images based on a 3D MRF model

Intensity-based classification of MR images has proven problematic, even when advanced techniques are used. The partial volume effect and the inhomogeneity are usually sources of difficulties. Here, the authors propose a new classification method using 3D MRF models and the multifractal dimension measure for segmenting CSF, gray matter and white matter in MR T1-weighted images. Mixclasses (mixture of two pure tissue classes) result from the partial volume effect, are taken into account in the authors´ tissue class model. Results are described with two acquisition sequences: IR-FGRE and SPGR. The accuracy of the classification is found by the way of a phantom validation study