PURE PHASE-ENCODED MRI AND CLASSIFICATION OF SOLIDS

In this work, we combine a pure phase-encoded Magnetic Resonance Imagi ng (MRI) method with a new tissue-classification technique to make geo metric models of a human tooth, We demonstrate the feasibility of thre e-dimensional imaging of solids using a conventional 11.7-T NMR spectr ometer. In solid-state imaging, confounding line-broadening effects ar e typically eliminated using coherent averaging methods. Instead, we c ircumvent them by detecting the proton signal at a fixed phase-encode time following the radio-frequency excitation. By a judicious choice o f the phase-encode time in the MR imaging protocol, we differentiate e namel and dentine sufficiently to successfully apply a new classificat ion algorithm. This: tissue-classification algorithm identifies the di stribution of different material types, such as enamel and dentine, in volumetric data. In this algorithm, we treat a voxel as a volume, not as a single point, and assume that each voxel may contain more than o ne material. We use the distribution of MR image intensities within ea ch voxel-sized volume to estimate the relative proportion of each mate rial using a probabilistic approach. This combined approach, involving MRT and data classification, is directly applicable to bone imaging a nd hard tissue contrast-based modeling of biological solids.