Variational segmentation of multi-channel MRI images

MRIs are effective for non-invasively imaging the interior of the human brain. Due to the large amount of data associated with typical MRI sessions, manual segmentation of the images of the human brain is prohibitive except in isolated cases. The various imaging and contrast artifacts common to MRIs, however, make automatic segmentation difficult. A segmentation algorithm incorporating multi-channel MRI data is described; this approach utilizes the variational calculus formulation to simultaneously compute piecewise smooth estimates of each channel, as well as a continuous “edge process” common to all the channels