Paper
3 July 2001 Template selection and rejection for robust nonrigid 3D registration in the presence of large deformations
Peter Roesch, Torsten Mohs, Thomas Netsch, Marcel J. Quist, Graeme P. Penney, David John Hawkes, Juergen Weese
Author Affiliations +
Abstract
The purpose of the proposed template propagation method is to support the comparative analysis of image pairs even when large deformations (e.g. from movement) are present. Starting from a position where valid starting estimates are known, small sub-volumes (templates) are registered rigidly. Propagating registration results to neighboring templates, the algorithm proceeds layer by layer until corresponding points for the whole volume are available. Template classification is important for defining the templates to be registered, for propagating registration results and for selecting successfully registered templates which finally represent the motion vector field. This contribution discusses a template selection and classification strategy based on the analysis of the similarity measure in the vicinity of the optimum. For testing the template propagation and classification methods, deformation fields of four volume pairs exhibiting considerable deformations have been estimated and the results have been compared to corresponding points picked by an expert. In all four cases, the proposed classification scheme was successful. Based on homologous points resulting from template propagation, an elastic transformation was performed.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter Roesch, Torsten Mohs, Thomas Netsch, Marcel J. Quist, Graeme P. Penney, David John Hawkes, and Juergen Weese "Template selection and rejection for robust nonrigid 3D registration in the presence of large deformations", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); https://doi.org/10.1117/12.431128
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Cited by 8 scholarly publications.
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KEYWORDS
Image registration

Image classification

3D image processing

Magnetic resonance imaging

Image quality

Lung

Image analysis

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