Biostatistics Research Today is a free monthly online journal that collates and summarizes the latest research about Biostatistics, including details on statistics, uncertainty, probability, modeling.

Digital diagnostics: Three-dimensional modelling.

Singh GD

BioModeling Solutions, 20699 NE Glisan Street # 233, Fairview, OR 97024, USA. info@biomodelings.com

Three-dimensional imaging techniques, such as computed tomograms (CT), structured light, and stereophotogrammetry, can be used to capture three-dimensional coordinate data, but comprehensive analysis is required to transform these techniques into powerful diagnostic tools. The object of this review is to highlight analytical functionality using software developed to study three-dimensional digital imaging and communications in medicine (DICOM) based digital data for diagnosis, planning of treatment, and evaluation of craniofacial changes. My specific aim was to apply three-dimensional software routines using geometric morphometrics or conventional measurements. These routines rely on robust algorithms to construct mean objects by manipulating the three-dimensional x, y, and z coordinates of all the objects' vertices. Conventional measurements and statistical tests can then be applied to the changes in the vertices, say, before and after treatment. Using graphical and geometric morphometric techniques such as finite-element analysis and principal components analysis, clinical craniofacial modelling can be used for the localisation and quantification of soft and hard tissue changes; diagnostic modelling can be undertaken for planning of treatment, and data-driven predictive modelling can be undertaken for the planning of many procedures based on the surgeon's own experience, patients, and resources. Three-dimensional modelling of digital data may therefore have added value for clinical diagnosis, and planning and assessment of treatment, including audit.

Published 24 December 2007 in Br J Oral Maxillofac Surg, 46(1): 22-6.
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