An evaluation of computer assisted skull re-assembly using hand held and automated laser scanners

Computer assisted skull re-assembly is an alternative to classical manual methods of physical restoration and reconstruction. The technique is reliant on high quality images produced by radiological CT or optical surface laser scans. The accuracy of CAD reassembly and the contribution the technologies of image production make to the process are largely unevaluated. This research uses four 3D models produced by a hand held laser scanner (Scorpion FASTSCAN by Polhemus) and one model produced by an automated, stationary laser scanner (Minolta by Hyperfocal) to re-assemble 5 skulls using a computer modelling program (Freeform Modelling). Hand held scanning, model production and quality are assessed; skull restoration accuracy is described and quantified by a reverse engineering software program (Geomagic Qualify) which measures overlap between the contour shells of original and restored skulls. The level of acceptable accuracy for skulls which might support facial reconstruction following re-assembly was determined to be < +/- 2.0 mm of error. Crania and mandibles were assessed individually. Accuracy results for five crania were unacceptable (40%), acceptable (40%), and reasonable (20%). Results for five mandibles demonstrated accuracy which was acceptable (40%), reasonable (20%), and good (40%). Optimising CAD potential for skull restoration depends on further research which examines: 1) the affect upon model quality resulting from the partnership between interdependent computer software, and 2) a comprehensive comparative analysis of surface capture technologies in relation to the models used in restoration.

Name dc:type.qualificationname

Master of Science

Level dc:type.qualificationlevel

Master's Thesis

Grantor dc:publisher.institution

University of Dundee

Year dc:date.issued

2007

Author dc:creator

• Mackenzie, Stenton

Language dc:language

eng

Identifier

oai:discovery.dundee.ac.uk:studenttheses/3ec039a4-5826-4d4b-9a63-b6c977938ac8

OAI identifier oai:identifier

oai:discovery.dundee.ac.uk:studenttheses/3ec039a4-5826-4d4b-9a63-b6c977938ac8