The signal intensity in a magnetic resonance image is not only a function of imaging parameters but also of several intrinsic tissue properties. Therefore, unlike other medical imaging modalities, magnetic resonance imaging (MRI) allows the imaging scientist to locate pathology using multispectral image segmentation. Multispectral image segmentation works best when orthogonal spectral regions are employed. In MRI, possible spectral regions are spin density (rho) , spin-lattice relaxation time T1, spin-spin relaxation time T2, and texture for each nucleus type and chemical shift. This study examines the ability of multispectral image segmentation to locate breast pathology using the total hydrogen T1, T2, and (rho) . The preliminary results indicate that our technique can locate cysts and fibroadenoma breast lesions with a minimum number of false-positives and false-negatives. Results, T1, T2, and (rho) algorithms, and segmentation techniques are presented.