The invention relates to automatic spatial context based multi-object segmentation in 3D images, in particular methods and systems for automatic classification of images of internal structures of human and animal bodies. A method includes receiving (405) a magnetic resonance (MR) image testing model and determining a testing volume of the testing model that includes areas of the testing model to be classified as bone or cartilage. The method includes modifying the testing model so that the testing volume corresponds to a mean shape and a shape variation space of an active shape model and producing an initial classification of the testing volume by fitting the testing volume to the mean shape and the shape variation space.; The method includes producing (425) a refined classification of the testing volume into bone areas and cartilage areas by refining the boundaries of the testing volume with respect to the active shape model and segmenting the MR image testing model into different areas corresponding to bone areas and cartilage areas.
Automatic spatial context based multi-object segmentation in 3D images