Automated identification of anatomical landmarks on 3D bone models reconstructed from CT scan images.

Identification of anatomical landmarks on skeletal tissue reconstructed from CT/MR images is indispensable in patient-specific preoperative planning (tumour referencing, deformity evaluation, resection planning, and implant alignment and anchoring) as well as intra-operative navigation (bone registration and instruments referencing). Interactive localisation of landmarks on patient-specific anatomical models is time-consuming and may lack in repeatability and accuracy. We present a computer graphics-based method for automatic localisation and identification (labelling) of anatomical landmarks on a 3D model of bone reconstructed from CT images of a patient. The model surface is segmented into different landmark regions (peak, ridge, pit and ravine) based on surface curvature. These regions are labelled automatically by an iterative process using a spatial adjacency relationship matrix between the landmarks. The methodology has been implemented in a software program and its results (automatically identified landmarks) are compared with those manually palpated by three experienced orthopaedic surgeons, on three 3D reconstructed bone models. The variability in location of landmarks was found to be in the range of 2.15-5.98 mm by manual method (inter surgeon) and 1.92-4.88 mm by our program. Both methods performed well in identifying sharp features. Overall, the performance of the automated methodology was better or similar to the manual method and its results were reproducible. It is expected to have a variety of applications in surgery planning and intra-operative navigation.