| 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 # |
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| Date of Issue |
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| Download PDF |
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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) |
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| Keyword(1) |
MRI |
| Keyword(2) |
brain tumor segmentation |
| Keyword(3) |
extended separable lattice hidden Markov model |
| Keyword(4) |
mathematical model |
| Keyword(5) |
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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 |
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Waseda University (Waseda Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2020-05-29 14:10:00 |
| Presentation Time |
20 minutes |
| Registration for |
IEICE-IE |
| Paper # |
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| Volume (vol) |
vol.44 |
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