Paper
13 March 2009 Experimental comparison of landmark-based methods for 3D elastic registration of pre- and postoperative liver CT data
Thomas Lange, Stefan Wörz, Karl Rohr, Peter M. Schlag
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Abstract
The qualitative and quantitative comparison of pre- and postoperative image data is an important possibility to validate surgical procedures, in particular, if computer assisted planning and/or navigation is performed. Due to deformations after surgery, partially caused by the removal of tissue, a non-rigid registration scheme is a prerequisite for a precise comparison. Interactive landmark-based schemes are a suitable approach, if high accuracy and reliability is difficult to achieve by automatic registration approaches. Incorporation of a priori knowledge about the anatomical structures to be registered may help to reduce interaction time and improve accuracy. Concerning pre- and postoperative CT data of oncological liver resections the intrahepatic vessels are suitable anatomical structures. In addition to using branching landmarks for registration, we here introduce quasi landmarks at vessel segments with high localization precision perpendicular to the vessels and low precision along the vessels. A comparison of interpolating thin-plate splines (TPS), interpolating Gaussian elastic body splines (GEBS) and approximating GEBS on landmarks at vessel branchings as well as approximating GEBS on the introduced vessel segment landmarks is performed. It turns out that the segment landmarks provide registration accuracies as good as branching landmarks and can improve accuracy if combined with branching landmarks. For a low number of landmarks segment landmarks are even superior.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Lange, Stefan Wörz, Karl Rohr, and Peter M. Schlag "Experimental comparison of landmark-based methods for 3D elastic registration of pre- and postoperative liver CT data", Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72610M (13 March 2009); https://doi.org/10.1117/12.811871
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Cited by 2 scholarly publications.
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KEYWORDS
Liver

Image registration

3D modeling

Image segmentation

Tumors

Data modeling

Matrices

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