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Proceedings Paper

Fast registration of pre- and peri-interventional CT images for targeting support in radiofrequency ablation of hepatic tumors
Author(s): J. Bieberstein; C. Schumann; A. Weihusen; T. Boehler; S. Wirtz; P. Bruners; D. Schmidt; C. Trumm; M. Niethammer; G. Haras; R.-T. Hoffmann; A. H. Mahnken; P. L. Pereira; H.-O. Peitgen
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Paper Abstract

Radiofrequency (RF) ablation is an image-guided minimally invasive therapy which destroys a tumor by locally inducing electrical energy into the malignant tissue through a radiofrequency applicator. Treatment success is essentially dependent on the accurate placement of the RF applicator. In the case of CT-guided RF ablation of liver tumors, a central problem during monitoring is the reduced quality and information content in the peri-interventional images compared to the images used for planning. Therefore, the question of how to effectively transfer information from the planning scan into the peri-interventional scan in order to support the interventionalist is of high interest. Key to such an enhancement of peri-interventional scans is an adequate registration of the pre- and peri-interventional image, which also needs to be fast since intervention duration is still a challenge. We present an approach for the fast and automatic registration of a high quality CT volume scan of the liver to a spiral CT scan of lower quality. Our method combines an approximate pre-registration to compensate large displacements and a rigid registration of a liver subvolume for further refinement. The method focuses on the position of the tumor to be ablated and the corresponding access path. Thereby, it achieves both fast and precise results in the region of interest. A preliminary evaluation, on 37 data sets from 20 different patients, shows that the registration is performed within a maximum of 18 seconds, while obtaining high accuracy in the relevant region of the liver comprising tumor and the planned access path.

Paper Details

Date Published: 13 March 2009
PDF: 11 pages
Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72610F (13 March 2009); doi: 10.1117/12.813523
Show Author Affiliations
J. Bieberstein, Fraunhofer MEVIS, Institute for Medical Image Computing (Germany)
C. Schumann, Fraunhofer MEVIS, Institute for Medical Image Computing (Germany)
A. Weihusen, Fraunhofer MEVIS, Institute for Medical Image Computing (Germany)
T. Boehler, Fraunhofer MEVIS, Institute for Medical Image Computing (Germany)
S. Wirtz, Fraunhofer MEVIS, Institute for Medical Image Computing (Germany)
P. Bruners, RWTH Aachen (Germany)
D. Schmidt, Univ. Hospital Tübingen (Germany)
C. Trumm, Ludwig-Maximilians-Univ. of Munich (Germany)
M. Niethammer, Siemens Medical Solutions GmbH (Germany)
G. Haras, Siemens Medical Solutions GmbH (Germany)
R.-T. Hoffmann, Ludwig-Maximilians-Univ. of Munich (Germany)
A. H. Mahnken, RWTH Aachen (Germany)
P. L. Pereira, SLK-Kliniken GmbH (Germany)
H.-O. Peitgen, Fraunhofer MEVIS, Institute for Medical Image Computing (Germany)


Published in SPIE Proceedings Vol. 7261:
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kenneth H. Wong, Editor(s)

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