Intracranial Boundary Detection and Radio Frequency Correction in Magnetic Resonance Images

Magnetic resonance imaging (MRI) is a noninvasive method for producing three-dimensional tomographic images of the human body. MRI is most often used for the detection of tumors, lesions, and other abnormalities in soft tissues, such as the brain. Several techniques for automatically segmenting brain tissues in MRI scans of the head have recently been developed. One goal of segmentation is to automatically or semiautomatically detect lesions in the brains of multiple sclerosis patients. The number and size of lesions indicate the progression of the disease in the patient. Therefore, automatic lesion detection may significantly aid in the analysis of treatments. Segmentation is problematic due to radio frequency inhomogeneity (image intensity variation) caused by inaccuracies in the magnetic resonance scanner and by nonuniform loading of the scanner coils by the patient. The segmentation algorithms also have difficulty dealing with tissues outside the brain, such as skin, fat, and bone...