Abstract: This paper presents the automated methods employed
for extracting craniofacial landmarks in white light images as part of
a registration framework designed to support three neurosurgical
procedures. The intraoperative space is characterised by white light
stereo imaging while the preoperative plan is performed on CT scans.
The registration aims at aligning these two modalities to provide a
calibrated environment to enable image-guided solutions. The
neurosurgical procedures can then be carried out by mapping the
entry and target points from CT space onto the patient-s space. The
registration basis adopted consists of natural landmarks (eye corner
and ear tragus). A 5mm accuracy is deemed sufficient for these three
procedures and the validity of the selected registration basis in
achieving this accuracy has been assessed by simulation studies. The
registration protocol is briefly described, followed by a presentation
of the automated techniques developed for the extraction of the
craniofacial features and results obtained from tests on the AR and
FERET databases. Since the three targeted neurosurgical procedures
are routinely used for head injury management, the effect of
bruised/swollen faces on the automated algorithms is assessed. A
user-interactive method is proposed to deal with such unpredictable
circumstances.