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Gauss-Newton Method for Segmentation assisted Deformable Registration

Birkfellner, Wolfgang, Fechter, Tobias, Furtado, Hugo, Hauler, Frida, Jurisic, Miro, Nestle, Ursula
Medical University of Vienna
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3492
Published in The MIDAS Journal - MICCAI 2014 Workshop: Image-Guided Adaptive Radiation Therapy (IGART).
Submitted by Miro Jurisic on 2014-10-20 11:15:24.

In this work, we try to develop a fast converging method for segmentation assisted deformable registration. The segmentation step consists of a piece-wise constant Mumford-Shah energy model while reg- istration is driven by the sum of squared distances of both initial images and segmented mask with a diffusion regularization. In order to solve this energy minimization problem, a second order Gauss-Newton opti- mization method is used. For the numerical experiments we used CT data sets from the EMPIRE10 challenge. In this preliminary study, we show high accuracy of our algorithm.