For any image guided surgery, independently of the technique
which is used (navigation, templates, robotics), it is necessary
to get a 3D bone surface model from CT or MR images.
Such model is used for planning, registration and visualization.
We report that graphical representation of patient
bony structure and the surgical tools, interconnectively
with the tracking device and patient-to-image registration are
crucial components in such a system. For Total Shoulder
Arthroplasty (TSA), there are many challenges, The most of
cases that we are working with are pathological cases such
as rheumatoid arthritis, osteoarthritis disease. The CT images
of these cases often show a fusion area between the
glenoid cavity and the humeral head. They also show severe
deformations of the humeral head surface that result in
a loss of contours. This fusion area and image quality problems
are also amplified by well-known CT-scan artifacts like
beam-hardening or partial volume effects. The state of the art
shows that several segmentation techniques, applied to CTScans
of the shoulder, have already been disclosed. Unfortunately,
their performances, when used on pathological data,
are quite poor [1, 2]. The aim of this paper is to present a
new image guided surgery system based on CT scan of the
patient and using bony structure recognition, morphological
analysis for the operated region and robust image-to-patient
registration.