
Proceedings Paper
Evaluation of non-rigid constrained CT/CBCT registration algorithms for delineation propagation in the context of prostate cancer radiotherapyFormat | Member Price | Non-Member Price |
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Paper Abstract
Image-Guided Radiation Therapy (IGRT) aims at increasing the precision of radiation dose delivery. In the context of prostate cancer, a planning Computed Tomography (CT) image with manually defined prostate and organs at risk (OAR) delineations is usually associated with daily Cone Beam Computed Tomography (CBCT) follow-up images. The CBCT images allow to visualize the prostate position and to reposition the patient accordingly. They also should be used to evaluate the dose received by the organs at each fraction of the treatment. To do so, the first step is a prostate and OAR segmentation on the daily CBCTs, which is very timeconsuming. To simplify this task, CT to CBCT non-rigid registration could be used in order to propagate the original CT delineations in the CBCT images. For this aim, we compared several non-rigid registration methods. They are all based on the Mutual Information (MI) similarity measure, and use a BSpline transformation model. But we add different constraints to this global scheme in order to evaluate their impact on the final results. These algorithms are investigated on two real datasets, representing a total of 70 CBCT on which a reference delineation has been realized. The evaluation is led using the Dice Similarity Coefficient (DSC) as a quality criteria. The experiments show that a rigid penalty term on the bones improves the final registration result, providing high quality propagated delineations.
Paper Details
Date Published: 8 March 2013
PDF: 6 pages
Proc. SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, 867106 (8 March 2013); doi: 10.1117/12.2004519
Published in SPIE Proceedings Vol. 8671:
Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes III; Ziv R. Yaniv, Editor(s)
PDF: 6 pages
Proc. SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, 867106 (8 March 2013); doi: 10.1117/12.2004519
Show Author Affiliations
Mathieu Rubeaux, INSERM (France)
Univ. de Rennes 1 (France)
Antoine Simon, INSERM (France)
Univ. de Rennes 1 (France)
Khemara Gnep, Ctr. Eugène Marquis (France)
Jérémy Colliaux, Ctr. Eugène Marquis (France)
Univ. de Rennes 1 (France)
Antoine Simon, INSERM (France)
Univ. de Rennes 1 (France)
Khemara Gnep, Ctr. Eugène Marquis (France)
Jérémy Colliaux, Ctr. Eugène Marquis (France)
Oscar Acosta, INSERM (France)
Univ. de Rennes 1 (France)
Renaud de Crevoisier, INSERM (France)
Univ. de Rennes 1 (France)
Ctr. Eugène Marquis (France)
Pascal Haigron, INSERM (France)
Univ. de Rennes 1 (France)
Univ. de Rennes 1 (France)
Renaud de Crevoisier, INSERM (France)
Univ. de Rennes 1 (France)
Ctr. Eugène Marquis (France)
Pascal Haigron, INSERM (France)
Univ. de Rennes 1 (France)
Published in SPIE Proceedings Vol. 8671:
Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes III; Ziv R. Yaniv, Editor(s)
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