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Proceedings Paper

Femur specific polyaffine model to regularize the log-domain demons registration
Author(s): Christof Seiler; Xavier Pennec; Lucas Ritacco; Mauricio Reyes
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Paper Abstract

Osteoarticular allograft transplantation is a popular treatment method in wide surgical resections with large defects. For this reason hospitals are building bone data banks. Performing the optimal allograft selection on bone banks is crucial to the surgical outcome and patient recovery. However, current approaches are very time consuming hindering an efficient selection. We present an automatic method based on registration of femur bones to overcome this limitation. We introduce a new regularization term for the log-domain demons algorithm. This term replaces the standard Gaussian smoothing with a femur specific polyaffine model. The polyaffine femur model is constructed with two affine (femoral head and condyles) and one rigid (shaft) transformation. Our main contribution in this paper is to show that the demons algorithm can be improved in specific cases with an appropriate model. We are not trying to find the most optimal polyaffine model of the femur, but the simplest model with a minimal number of parameters. There is no need to optimize for different number of regions, boundaries and choice of weights, since this fine tuning will be done automatically by a final demons relaxation step with Gaussian smoothing. The newly developed synthesis approach provides a clear anatomically motivated modeling contribution through the specific three component transformation model, and clearly shows a performance improvement (in terms of anatomical meaningful correspondences) on 146 CT images of femurs compared to a standard multiresolution demons. In addition, this simple model improves the robustness of the demons while preserving its accuracy. The ground truth are manual measurements performed by medical experts.

Paper Details

Date Published: 10 March 2011
PDF: 6 pages
Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79620G (10 March 2011); doi: 10.1117/12.878316
Show Author Affiliations
Christof Seiler, Univ. Bern (Switzerland)
INRIA Sophia Antipolis (France)
Xavier Pennec, INRIA Sophia Antipolis (France)
Lucas Ritacco, Hospital Italiano de Buenos Aires (Argentina)
Mauricio Reyes, Univ. Bern (Switzerland)

Published in SPIE Proceedings Vol. 7962:
Medical Imaging 2011: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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