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3D ultrasound-CT registration of the liver using combined landmark-intensity information

Item Type:Article
Title:3D ultrasound-CT registration of the liver using combined landmark-intensity information
Creators Name:Lange, T. and Papenberg, N. and Heldmann, S. and Modersitzki, J. and Fischer, B. and Lamecker, H. and Schlag, P.M.
Abstract:PURPOSE: An important issue in computer-assisted surgery of the liver is a fast and reliable transfer of preoperative resection plans to the intraoperative situation. One problem is to match the planning data, derived from preoperative CT or MR images, with 3D ultrasound images of the liver, acquired during surgery. As the liver deforms significantly in the intraoperative situation non-rigid registration is necessary. This is a particularly challenging task because pre- and intraoperative image data stem from different modalities and ultrasound images are generally very noisy. METHODS: One way to overcome these problems is to incorporate prior knowledge into the registration process. We propose a method of combining anatomical landmark information with a fast non-parametric intensity registration approach. Mathematically, this leads to a constrained optimization problem. As distance measure we use the normalized gradient field which allows for multimodal image registration. RESULTS: A qualitative and quantitative validation on clinical liver data sets of three different patients has been performed. We used the distance of dense corresponding points on vessel center lines for quantitative validation. The combined landmark and intensity approach improves the mean and percentage of point distances above 3 mm compared to rigid and thin-plate spline registration based only on landmarks. CONCLUSION: The proposed algorithm offers the possibility to incorporate additional a priori knowledge-in terms of few landmarks-provided by a human expert into a non-rigid registration process.
Keywords:Algorithms, Hepatectomy, Computer-Assisted Image Interpretation, Three-Dimensional Imaging, Liver Neoplasms, Predictive Value of Tests, Reproducibility of Results, Computer-Assisted Surgery, X-Ray Computed Tomography
Source:International Journal of Computer Assisted Radiology and Surgery
ISSN:1861-6410
Publisher:Springer (Germany)
Volume:4
Number:1
Page Range:79-88
Date:January 2009
Official Publication:https://doi.org/10.1007/s11548-008-0270-1
PubMed:View item in PubMed

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