Evaluation of Bone Contrast Enhanced MRI Sequences and Voxel Based Segmentation

Abstract: An ultra-short echo time (UTE) magnetic resonance imaging (MRI) sequence was used together with other MRI sequences to evaluate the possibility of segmenting air, soft tissues and bone. Three patients were imaged with the UTE sequence and other sequences as well as with computed tomography (CT). An algorithm using Gaussian mixture models was developed and applied to the problem of segmenting the MR images. A similar algorithm was developed and used to generate an artificial CT image from the MR data. The images of the first patient were used as training data for the algorithms and the images of the other two patients were used for validation. It was found that less than 20 percent of the volume inside the head was misclassified and that the root mean square error of the artificial CT image was less than 420 Hounsfield units. Finally a volunteer was imaged in the same way but with an additional UTE sequence with a larger flip angle. The results suggested that the additional image may improve segmentation further.