@inproceedings{LameckerSeebassHegeetal.2004, author = {Lamecker, Hans and Seebaß, Martin and Hege, Hans-Christian and Deuflhard, Peter}, title = {A 3d statistical shape model of the pelvic bone for segmentation}, series = {Proc. SPIE Medical Imaging 2004}, volume = {5370}, booktitle = {Proc. SPIE Medical Imaging 2004}, editor = {Fitzpatrick, J. and Sonka, Milan}, pages = {1341 -- 1351}, year = {2004}, language = {en} } @inproceedings{LameckerSeebassHegeetal.2004, author = {Lamecker, Hans and Seebaß, Martin and Hege, Hans-Christian and Deuflhard, Peter}, title = {A 3D statistical shape model of the pelvic bone for segmentation}, series = {Proceedings of SPIE - Volume 5370 Medical Imaging 2004}, booktitle = {Proceedings of SPIE - Volume 5370 Medical Imaging 2004}, editor = {Fitzpatrick, J. and Sonka, Milan}, doi = {10.1117/12.534145}, pages = {1341 -- 1351}, year = {2004}, language = {en} } @inproceedings{LangeWenckebachSeebassetal.2004, author = {Lange, Thomas and Wenckebach, Thomas and Seebaß, Martin and Lamecker, Hans and H{\"u}nerbein, Michael}, title = {Registration of different phases of contrast-enhanced MR data for liver surgery}, series = {3. Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer-Roboterassistierte Chirurgie CURAC}, booktitle = {3. Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer-Roboterassistierte Chirurgie CURAC}, year = {2004}, language = {en} } @misc{LameckerLangeSeebass, author = {Lamecker, Hans and Lange, Thomas and Seebass, Martin}, title = {Segmentation of the Liver using a 3D Statistical Shape Model}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-7847}, number = {04-09}, abstract = {This paper presents an automatic approach for segmentation of the liver from computer tomography (CT) images based on a 3D statistical shape model. Segmentation of the liver is an important prerequisite in liver surgery planning. One of the major challenges in building a 3D shape model from a training set of segmented instances of an object is the determination of the correspondence between different surfaces. We propose to use a geometric approach that is based on minimizing the distortion of the correspondence mapping between two different surfaces. For the adaption of the shape model to the image data a profile model based on the grey value appearance of the liver and its surrounding tissues in contrast enhanced CT data was developed. The robustness of this method results from a previous nonlinear diffusion filtering of the image data. Special focus is turned to the quantitative evaluation of the segmentation process. Several different error measures are discussed and implemented in a study involving more than 30 livers.}, language = {en} } @inproceedings{SeebassLameckerGellermannetal.2004, author = {Seebaß, Martin and Lamecker, Hans and Gellermann, Johanna and Wust, Peter}, title = {The impact of segmentation accuracy on treatment planning for regional hyperthermia}, series = {Proceedings of the 9th International Congress on Hyperthermic Oncology}, booktitle = {Proceedings of the 9th International Congress on Hyperthermic Oncology}, year = {2004}, language = {en} } @inproceedings{LameckerSeebassLangeetal.2004, author = {Lamecker, Hans and Seebass, Martin and Lange, Thomas and Hege, Hans-Christian and Deuflhard, Peter}, title = {Visualization of the variability of 3D statistical shape models by animation}, series = {Proc. Medicine Meets Virtual Reality}, volume = {98}, booktitle = {Proc. Medicine Meets Virtual Reality}, editor = {Westwood, J.}, publisher = {IOS Press}, pages = {190 -- 196}, year = {2004}, language = {en} }