Presentation 2009-07-15
Metastatic Liver Tumor Segmentation from Plain and Contrast Enhanced Computed Tomography
Takuya NARIHIRA, Akinobu SHIMIZU, Hidefumi KOBATAKE, Shigeru NAWANO, Kenji SHINOZAKI,
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Abstract(in English) This paper presents an automated metastatic liver tumor segmentation process from plane and portal venous CT volumes. First we propose an automated segmentation method based on shape constrained graph cut algorithm to extract sidewall of body cavity, diaphragm and liver. Multi phase CT volumes provide helpful information in diagnosis. However, it is difficult for a single process to use the information effectively. We have aimed to develop an accurate process by combining many weak segmentation processes using a boosting algorithm. This paper shows the results of evaluating these algorithms by cross-validation using 20 set of CT volumes.
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Keyword(in English) CT image / boosting / liver / metastatic tumor / segmentation / graph cut / statistical shape model
Paper # MI2009-54
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Committee MI
Conference Date 2009/7/8(1days)
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Paper Information
Registration To Medical Imaging (MI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Metastatic Liver Tumor Segmentation from Plain and Contrast Enhanced Computed Tomography
Sub Title (in English)
Keyword(1) CT image
Keyword(2) boosting
Keyword(3) liver
Keyword(4) metastatic tumor
Keyword(5) segmentation
Keyword(6) graph cut
Keyword(7) statistical shape model
1st Author's Name Takuya NARIHIRA
1st Author's Affiliation Tokyo University of Agriculture and Technology()
2nd Author's Name Akinobu SHIMIZU
2nd Author's Affiliation Tokyo University of Agriculture and Technology
3rd Author's Name Hidefumi KOBATAKE
3rd Author's Affiliation Tokyo University of Agriculture and Technology
4th Author's Name Shigeru NAWANO
4th Author's Affiliation Center for Radiological Sciences, International University of Health and Welfare
5th Author's Name Kenji SHINOZAKI
5th Author's Affiliation National Kyusyu Cancer Center
Date 2009-07-15
Paper # MI2009-54
Volume (vol) vol.109
Number (no) 127
Page pp.pp.-
#Pages 6
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