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Paper Abstract and Keywords
Presentation 2020-05-29 14:10
Construction of Hidden Markov Models for Brain Tumor Segmentation
Takuya Honda, Yuta Nakahara, Matushima Toshiyasu (Waseda Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) Brain tumor segmentation is one of the systems that a computer, which has attracted attention in recent years, assists doctors in diagnosis. Conventionally, the mainstream method is to obtain a threshold value for judging whether a tumor is a tumor from the pixel values of the brain image.In this study, we proposed a two-level hidden Markov model to express the mechanism of brain tumor development and the physical structure of the human brain, and expressed brain MRI with tumor. In this way, it is possible to make use of the data to make use of the background knowledge of the data to solve various problems.
In this study, this model was formulated as a state estimation problem, and the optimal decision was derived under Bayesian criteria. After that, we derived an efficient approximation algorithm.
Keyword (in Japanese) (See Japanese page) 
(in English) MRI / brain tumor segmentation / extended separable lattice hidden Markov model / mathematical model / / / /  
Reference Info. ITE Tech. Rep.
Paper #  
Date of Issue  
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
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Conference Information
Committee IEICE-MI IEICE-IE IEICE-SIP IEICE-BioX IST ME  
Conference Date 2020-05-28 - 2020-05-29 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image and signal processing/analysis/AI technology, and their application 
Paper Information
Registration To IEICE-IE 
Conference Code 2020-05-MI-IE-SIP-BioX-IST-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Construction of Hidden Markov Models for Brain Tumor Segmentation 
Sub Title (in English)  
Keyword(1) MRI  
Keyword(2) brain tumor segmentation  
Keyword(3) extended separable lattice hidden Markov model  
Keyword(4) mathematical model  
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1st Author's Name Takuya Honda  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Yuta Nakahara  
2nd Author's Affiliation Waseda University (Waseda Univ.)
3rd Author's Name Matushima Toshiyasu  
3rd Author's Affiliation Waseda University (Waseda Univ.)
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Speaker
Date Time 2020-05-29 14:10:00 
Presentation Time 20 
Registration for IEICE-IE 
Paper #  
Volume (vol) ITE-44 
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#Pages ITE- 
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