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BY-NC-ND 3.0 license Open Access Published by De Gruyter Open Access March 1, 2007

Image-to-patient registration by natural anatomical surfaces of the head

  • Rüdiger Marmulla EMAIL logo , Joachim Mühling and Georg Eggers
From the journal Open Medicine

Abstract

The use of registration markers in computer-assisted surgery is combined with high logistic costs and efforts.

During the preparation of image guided surgery, automated markerless patient-to-image registration based on anatomical surfaces allows a significant reduction of preoperative effort and of the radiation dose the patient is exposed to. Placement and measurement of radio-opaque fiducial markers becomes unnecessary. The usability of face, auricle, maxilla and mandible for surface-based registration to CT image data was investigated. The present study was performed to evaluate the clinical accuracy in finding defined target points within the surgical site after markerless patient registration in image-guided oral and maxillofacial surgery.

Preoperatively, the spatial position of 20 patients was registered to CT image data using a 3D laser surface scanner. Indications for surgery were tumours, foreign bodies and skeletal malformations. The accuracy of this surface-based registration was verified using additionally placed fiducial markers.

The study showed, that markerless surface-based registration was sufficiently accurate for clinical use when the surface used for matching was the upper jaw, the face, or — with reservations — the auricle. Surface-based registration using the mandible did not yield satisfying results. To conclude, image-to-patient registration based on laser surface scanning is a valuable method for surgery of the head. Multiple sites of the head were identified as appropriate for the method. Hence, dependent on the individual case and the intended surgery, the registration area can be selected with the necessary flexibility.

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Published Online: 2007-3-1
Published in Print: 2007-3-1

© 2007 Versita Warsaw

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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