Discriminative, Semantic Segmentation of Brain Tissue in MR Images - Yi, Zhao; Criminisi, Antonio; Shotton, Jamie; Blake, Andrew (MICCAI 2009, 2009)
A new algorithm is presented for the automatic segmentation and classiﬁcation of brain tissue from 3D MR scans. It uses discriminative Random Decision Forest classiﬁcation and takes into account partial volume eﬀects. This is combined with correction of intensities for the MR bias ﬁeld, in conjunction with a learned model of spatial context, to achieve accurate voxel-wise classiﬁcation. Our quantitative validation, carried out on existing labelled datasets, demonstrates improved results over the state of the art, especially for the cerebro-spinal ﬂuid class which is the most diﬃcult to label accurately