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Proceedings Paper

3D registration of surfaces for change detection in medical images
Author(s): Elizabeth Fisher; Paul F. van der Stelt; Stanley M. Dunn
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Paper Abstract

Spatial registration of data sets is essential for quantifying changes that take place over time in cases where the position of a patient with respect to the sensor has been altered. Changes within the region of interest can be problematic for automatic methods of registration. This research addresses the problem of automatic 3D registration of surfaces derived from serial, single-modality images for the purpose of quantifying changes over time. The registration algorithm utilizes motion-invariant, curvature- based geometric properties to derive an approximation to an initial rigid transformation to align two image sets. Following the initial registration, changed portions of the surface are detected and excluded before refining the transformation parameters. The performance of the algorithm was tested using simulation experiments. To quantitatively assess the registration, random noise at various levels, known rigid motion transformations, and analytically-defined volume changes were applied to the initial surface data acquired from models of teeth. These simulation experiments demonstrated that the calculated transformation parameters were accurate to within 1.2 percent of the total applied rotation and 2.9 percent of the total applied translation, even at the highest applied noise levels and simulated wear values.

Paper Details

Date Published: 25 April 1997
PDF: 12 pages
Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); doi: 10.1117/12.274146
Show Author Affiliations
Elizabeth Fisher, Cleveland Clinic Foundation (United States)
Paul F. van der Stelt, Academic Ctr. for Dentistry (Netherlands)
Stanley M. Dunn, Rutgers Univ. (United States)


Published in SPIE Proceedings Vol. 3034:
Medical Imaging 1997: Image Processing
Kenneth M. Hanson, Editor(s)

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