Presentation 2009-05-28
Registration of Non-Rigit Surface in Medical Image Based on Probabilistic Estimation of Feature-Points' Location
Wataru WATANABE, Hidekata HONTANI, Tohoru TAKEDA, Yorihisa WATANABE,
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Abstract(in English) This article proposes a new method for registering a surface of an organ in a 3D medical image with a surface mesh model of the surface. Each grid point of the surface mesh has probabilistic models of its position, the local deformation, and its local image pattern. For learning those probabilistic models, we compute a set of correspondences on each surface of sample data by using an entropy-based particle system. For the registration, we use a non-parametric belief propagation. The proposed method can estimate the probability density distribution of the position of each grid of the surface mesh. The proposed method was applied to some actual 3D medical images, and the results are presented in this article.
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Keyword(in English) Computer Aided Diagnosis / CT image / Organ segmentation / Registration / Belief propagation
Paper # IE2009-16,PRMU2009-7,MI2009-7
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Conference Information
Committee PRMU
Conference Date 2009/5/21(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) Registration of Non-Rigit Surface in Medical Image Based on Probabilistic Estimation of Feature-Points' Location
Sub Title (in English)
Keyword(1) Computer Aided Diagnosis
Keyword(2) CT image
Keyword(3) Organ segmentation
Keyword(4) Registration
Keyword(5) Belief propagation
1st Author's Name Wataru WATANABE
1st Author's Affiliation Nagoya Insutitute of Technology()
2nd Author's Name Hidekata HONTANI
2nd Author's Affiliation Nagoya Insutitute of Technology
3rd Author's Name Tohoru TAKEDA
3rd Author's Affiliation Tsukuba University
4th Author's Name Yorihisa WATANABE
4th Author's Affiliation Yamagata Saisei Hospital
Date 2009-05-28
Paper # IE2009-16,PRMU2009-7,MI2009-7
Volume (vol) vol.109
Number (no) 64
Page pp.pp.-
#Pages 6
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