| Presentation | 2020-05-29 Construction of Hidden Markov Models for Brain Tumor Segmentation Takuya Honda, Yuta Nakahara, Matushima Toshiyasu, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(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) |
| Keyword(in English) | MRI / brain tumor segmentation / extended separable lattice hidden Markov model / mathematical model |
| Paper # | SIP2020-13,BioX2020-13,IE2020-13,MI2020-13 |
| Date of Issue | 2020-05-21 (SIP, BioX, IE, MI) |
| Conference Information | |
| Committee | MI / IE / SIP / BioX / ITE-IST / ITE-ME |
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| Conference Date | 2020/5/28(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | 会議ツールは未定 |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Image and signal processing/analysis/AI technology, and their application |
| Chair | Yoshiki Kawata(Tokushima Univ.) / Hideaki Kimata(NTT) / Naoyuki Aikawa(TUS) / Akira Otsuka(IISEC) / Shigetoshi Sugawa(Tohoku Univ.) / Arai Hiroyuki(Nippon Institute of Technology) |
| Vice Chair | Takayuki Kitasaka(Aichi Inst. of Tech.) / Hidekata Hontani(Nagoya Inst. of Tech.) / Kazuya Kodama(NII) / Keita Takahashi(Nagoya Univ.) / Kazunori Hayashi(Osaka City Univ) / Yukihiro Bandou(NTT) / Tetsushi Ohki(Shizuoka Univ.) / Takahiro Aoki(Fujitsu Labs.) / Takayuki Hamamoto(Tokyo Univ. of Science) |
| Secretary | Takayuki Kitasaka(Yamaguchi Univ.) / Hidekata Hontani(Univ. of Hyogo) / Kazuya Kodama(NTT) / Keita Takahashi(NHK) / Kazunori Hayashi(Hiroshima Univ.) / Yukihiro Bandou(Hosei Univ.) / Tetsushi Ohki(Univ. of Electro-Comm.) / Takahiro Aoki(SECOM) / Takayuki Hamamoto(Saitama Univ.) / (Panasonic) |
| Assistant | Hotaka Takizawa(Tsukuba Univ.) / Yoshito Otake(NAIST) / Kyohei Unno(KDDI Research) / Norishige Fukushima(Nagoya Inst. of Tech.) / Kenjiro Sugimoto(Waseda Univ.) / Daishi Watabe(Saitama Inst. of Tech.) / Ryota Horie(Shibaura Inst. of Tech.) |
| Paper Information | |
| Registration To | Technical Committee on Medical Imaging / Technical Committee on Image Engineering / Technical Committee on Signal Processing / Technical Committee on Biometrics / Technical Group on Information Sensing Technologies / Technical Group on Media Engineering |
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| Language | JPN |
| 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 |
| 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.) |
| Date | 2020-05-29 |
| Paper # | SIP2020-13,BioX2020-13,IE2020-13,MI2020-13 |
| Volume (vol) | vol.120 |
| Number (no) | SIP-38,BioX-37,IE-39,MI-40 |
| Page | pp.pp.61-66(SIP), pp.61-66(BioX), pp.61-66(IE), pp.61-66(MI), |
| #Pages | 6 |
| Date of Issue | 2020-05-21 (SIP, BioX, IE, MI) |