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A Deformable Model using Probabalistic Labelling and Surface Relaxation to Segment MR Volumes

Deformable models often require some degree of user-interaction to produce an accurate segmentation of the feature object. We propose an automatic deformable surface for segmenting the femur from magnetic resonance volumes of the knee. In order to overcome the limitations of many existing deformable models, probabilistic labelling is used to drive the deformation process, together with a surface relaxation phase to prevent self-intersection and leakage. Results are presented for the segmentation of the femur from knee MR volumes.