Segmentation of Liver Metastases in CT Scans by Adaptive Thresholding and Morphological Processing
Moltz, Jan Hendrik, Bornemann, Lars, Dicken, Volker, Peitgen, Heinz-Otto
MeVis Research GmbH, Bremen, Germany
Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/1419
New: Prefer using the following doi: https://doi.org/10.54294/msg94u
Submitted by Jan hendrik Moltz on 2008-07-07T19:34:55Z.
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.
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