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Proceedings Paper

Automatic estimation of registration parameters: image similarity and regularization
Author(s): T. R. Langerak; U. A. van der Heide; A. N. T. J. Kotte; J. P. W. Pluim
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Paper Abstract

Image registration is a procedure to spatially align two images that is often used in, for example, computer-aided diagnosis or segmentation applications. To maximize the flexibility of image registration methods, they depend on many registration parameters that must be fine-tuned for each specific application. Tuning parameters is a time-consuming task, that would ideally be performed for each individual registration. However, doing this manually for each registration is too time-consuming, and therefore we would like to do this automatically. This paper proposes a methodology to estimate one of most important parameters in a registration procedure, the regularization setting, on the basis of the image similarity. We test our method on a set of images of prostate cancer patients and show that using the proposed methodology, we can improve the result of image registration when compared to using an average-best parameter.

Paper Details

Date Published: 13 March 2010
PDF: 8 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76232S (13 March 2010); doi: 10.1117/12.844180
Show Author Affiliations
T. R. Langerak, Univ. Medical Ctr. Utrecht (Netherlands)
U. A. van der Heide, Univ. Medical Ctr. Utrecht (Netherlands)
A. N. T. J. Kotte, Univ. Medical Ctr. Utrecht (Netherlands)
J. P. W. Pluim, Univ. Medical Ctr. Utrecht (Netherlands)


Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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