Presentation 2005-05-20
Probabilistic liver-atlas construction based on diaphragm deforming and atlas-based liver segmentation from torso CT images
Teruhiko Kitagawa, Kazumasa Okuo, Xiangrong Zhou, Ryujiro Yokoyama, Takeshi Hara, Hiroshi Fujita, Masayuki Kanematsu, Hiroaki Hoshi,
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Abstract(in English) The normal anatomical structure recognition is very useful and necessary in computer-aided diagnosis system. This study proposes a method for automated generation of probabilistic atlas of liver region using non-contrast torso CT images which is a new approach for anatomical structure recognition in CAD development. In order to generate a precise probabilistic atlas, normalizing the anatomical structures in different patient cases is very important. We developed a new method to normalize the liver positions and shapes based on diaphragm deforming and create a particular probabilistic atlas for a patient dynamically and automatically. A fully-automated atlas-based liver segmentation method is developed and evaluated with a lot of CT images finally to show the validation and usefulness of the generated probabilistic atlas for CAD development.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Computer-aided diagnosis (CAD) / torso CT images / Probabilistic atlas / Automated liver segmentation / Diaphragm
Paper # PRMU2005-16,MI2005-16
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Conference Information
Committee PRMU
Conference Date 2005/5/13(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Probabilistic liver-atlas construction based on diaphragm deforming and atlas-based liver segmentation from torso CT images
Sub Title (in English)
Keyword(1) Computer-aided diagnosis (CAD)
Keyword(2) torso CT images
Keyword(3) Probabilistic atlas
Keyword(4) Automated liver segmentation
Keyword(5) Diaphragm
1st Author's Name Teruhiko Kitagawa
1st Author's Affiliation Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University()
2nd Author's Name Kazumasa Okuo
2nd Author's Affiliation Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University
3rd Author's Name Xiangrong Zhou
3rd Author's Affiliation Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University
4th Author's Name Ryujiro Yokoyama
4th Author's Affiliation Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University
5th Author's Name Takeshi Hara
5th Author's Affiliation Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University
6th Author's Name Hiroshi Fujita
6th Author's Affiliation Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University
7th Author's Name Masayuki Kanematsu
7th Author's Affiliation Department of Radiology, Gifu University School of Medicine and University Hospital
8th Author's Name Hiroaki Hoshi
8th Author's Affiliation Department of Radiology, Gifu University School of Medicine and University Hospital
Date 2005-05-20
Paper # PRMU2005-16,MI2005-16
Volume (vol) vol.105
Number (no) 63
Page pp.pp.-
#Pages 6
Date of Issue