{"version":1,"kind":"Article","sha256":"","slug":"584","location":"","dependencies":[],"doi":"10.54294/msg94u","frontmatter":{"title":"Segmentation of Liver Metastases in CT Scans by Adaptive Thresholding and Morphological Processing","abstract":"This article presents an algorithm for the segmentation of liver metastases in CT scans. It is a hybrid method that combines adaptive thresholding based on a gray value analysis of the ROI with model-based morphological processing. We show the results of the MICCAI liver tumor segmentation competition 2008 which were successful for all ten tumors.","license":"You are licensing your work to Kitware Inc. under the\nCreative Commons Attribution License Version 3.0.\n\nKitware Inc. agrees to the following:\n\nKitware is free\n * to copy, distribute, display, and perform the work\n * to make derivative works\n * to make commercial use of the work\n\nUnder the following conditions:\n\\\"by Attribution\\\" - Kitware must attribute the work in the manner specified by the author or licensor.\n\n * For any reuse or distribution, they must make clear to others the license terms of this work.\n * Any of these conditions can be waived if they get permission from the copyright holder.\n\nYour fair use and other rights are in no way affected by the above.\n\nThis is a human-readable summary of the Legal Code (the full license) available at\nhttp://creativecommons.org/licenses/by/3.0/legalcode","keywords":["MICCAI competition","segmentation","liver metastases"],"authors":[{"name":"Moltz, Jan Hendrik","email":"jan.moltz@mevis.de","affiliations":["MeVis Research GmbH, Bremen, Germany"],"corresponding":true},{"name":"Bornemann, Lars","affiliations":[]},{"name":"Dicken, Volker","email":"volker.dicken@mevis.fraunhofer.de","affiliations":[]},{"name":"Peitgen, Heinz-Otto","affiliations":[]}],"date_submitted":"2008-07-07T19:34:55Z","external_publication_id":584,"revision_cids":["bafkreif5vn2a3zy5ezqovzihwmtmyza4sm57rfcjio64jvvnexxnlxsd7u"]},"mdast":{"type":"root"},"downloads":[{"url":"https://ipfs.desci.com/ipfs/bafkreielwynv7xp5gchptvmzyhpzjt3bbt4a573ehjsmrzs7xzls5hlwh4","title":"root/reviews.md","filename":"reviews.md","extra":{"size_bytes":925,"type":"file"}},{"url":"https://ipfs.desci.com/ipfs/bafkreigajpdwmrkz25thfk2qgwoh3gykd5ifcvyyzsujbca4iemu3rq5ji","title":"root/insight-journal-metadata.json","filename":"insight-journal-metadata.json","extra":{"size_bytes":6833,"type":"file"}},{"url":"https://dweb.link/ipfs/bafybeibtp2latvigekqpkmdeehedzgst6l2wuwjopgs3dip2v35iefx3gq","title":"root/article.pdf","filename":"article.pdf","extra":{"size_bytes":1805611,"type":"file"}}],"references":{"cite":{"order":["ref1","ref2","ref3","ref4","ref5","ref6","ref7","ref8","ref9"]},"data":{"ref1":{"label":"ref1","enumerator":"1","url":"https://doi.org/10.1109/iembs.2005.1617181","html":"Liver tumor volume estimation by semiautomatic segmentation method+In: Proc. IEEE EMBS+2005+3296+3299+R. Lu+P. Marziliano+C.H. Thng"},"ref2":{"label":"ref2","enumerator":"2","url":"https://doi.org/10.1007/11428831_116","html":"Automatic hepatic tumor segmentation using statistical optimal threshold+In: Proc. ICCS+2005+934+940+S.J. Park+K.S. Seo+J.A. Park"},"ref3":{"label":"ref3","enumerator":"3","url":"https://doi.org/10.1007/978-3-540-73055-2_8","html":"Automatic segmentation of single and multiple neoplastic hepatic lesions in CT images+In: Proc. IWINAC+2007+63+71+M. Ciecholewski+M.R. Ogiela"},"ref4":{"label":"ref4","enumerator":"4","url":"https://doi.org/10.1109/icpr.2006.93","html":"A machine learning approach for locating boundaries of liver tumors in ct images+In: Proc. ICPR+2006+400+403+Y. Li+S. Hara+K.: Shimura"},"ref5":{"label":"ref5","enumerator":"5","url":"https://doi.org/10.1117/12.770516","html":"Simultaneous detection of multiple elastic surfaces with application to tumor segmentation in CT images+In: Proc. SPIE+6914+K. Li+M.P. Jolly"},"ref6":{"label":"ref6","enumerator":"6","url":"https://doi.org/10.1109/isbi.2008.4541116","html":"3d general lesion segmentation in CT+In: Proc. ISBI+2008+796+799+M.P. Jolly+L. Grady"},"ref7":{"label":"ref7","enumerator":"7","url":"https://doi.org/10.1007/s11548-006-0059-z","html":"OncoTREAT: a software assistant for cancer therapy monitoring+Int. J. CARS+231+5+2007+242+L. Bornemann+V. Dicken+J.M. Kuhnigk+D. Wormanns+H.O. Shin+H.C. Bauknecht+V. Diehl+M. Fabel+S. Meier+O. Kress+S. Krass+H.O.: Peitgen"},"ref8":{"label":"ref8","enumerator":"8","url":"https://doi.org/10.1109/tmi.2006.871547","html":"Morphological segmentation and partial volume analysis for volumetry of solid pulmonary lesions in thoracic CT scans+IEEE Trans. Med+417+4+2006+434+J.M. Kuhnigk+V. Dicken+L. Bornemann+A. Bakai+D. Wormanns+S. Krass+H.O. Peitgen"},"ref9":{"label":"ref9","enumerator":"9","html":"3d liver tumor segmentation challenge 2008+T. Niessen+C. Metz+M. Schaap+M. Styner+War eld+X. Deng+Heimann+B. van Ginneken"}}}}