High-accuracy patient-to-image registration for the facilitation of image-guided robotic microsurgery on the head

Gerber, Nicolas; Gavaghan, Kate; Bell, Brett; Williamson, Tom; Weisstanner, Christian; Caversaccio, Marco; Weber, Stefan (2013). High-accuracy patient-to-image registration for the facilitation of image-guided robotic microsurgery on the head. IEEE transactions on biomedical engineering, 60(4), pp. 960-8. New York, N.Y.: Institute of Electrical and Electronics Engineers IEEE 10.1109/TBME.2013.2241063

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Image-guided microsurgery requires accuracies an order of magnitude higher than today's navigation systems provide. A critical step toward the achievement of such low-error requirements is a highly accurate and verified patient-to-image registration. With the aim of reducing target registration error to a level that would facilitate the use of image-guided robotic microsurgery on the rigid anatomy of the head, we have developed a semiautomatic fiducial detection technique. Automatic force-controlled localization of fiducials on the patient is achieved through the implementation of a robotic-controlled tactile search within the head of a standard surgical screw. Precise detection of the corresponding fiducials in the image data is realized using an automated model-based matching algorithm on high-resolution, isometric cone beam CT images. Verification of the registration technique on phantoms demonstrated that through the elimination of user variability, clinically relevant target registration errors of approximately 0.1 mm could be achieved.

Item Type:

Journal Article (Original Article)

Division/Institute:

10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Image Guided Therapy
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Ear, Nose and Throat Disorders (ENT)
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Hearing Research Laboratory
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology

UniBE Contributor:

Gerber, Nicolas, Gerber, Kate, Bell, Brett, Williamson, Tom, Weisstanner, Christian, Caversaccio, Marco, Weber, Stefan (B)

Subjects:

600 Technology > 610 Medicine & health

ISSN:

0018-9294

Publisher:

Institute of Electrical and Electronics Engineers IEEE

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:36

Last Modified:

29 Mar 2023 23:32

Publisher DOI:

10.1109/TBME.2013.2241063

PubMed ID:

23340586

Web of Science ID:

000316812200012

URI:

https://boris.unibe.ch/id/eprint/14354 (FactScience: 221305)

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