We present a method for fully automatic segmentation ofthe bones and cartilages of the human knee from MRI data. Based onstatistical shape models and graph-based optimization, first the femoraland tibial bone surfaces are reconstructed. Starting from the bone sur-faces the cartilages are segmented simultaneously with a multi objecttechnique using prior knowledge on the variation of cartilage thickness.We validate our method on 40 clinical MRI datasets acquired before kneereplacement.
This work won the 2nd prize in the category “Automatic Knee/Cartilage Segmentation” at the MICCAI grand challenge workshop, see results.