| Presentation | 2021-11-05 Performance Improvement of Alzheimer's Disease Identification Using Cognitive Function Test Scores Daiki Endo, Koichi Ito, Takafumi Aoki, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | As the population ages, the prevalence of Alzheimer’s disease (AD) is expected to increase. AD causes progressive brain atrophy, making it difficult to perform even simple daily tasks. Although medical advances have made it possible to control the progression of AD with medication, it is necessary to detect AD in its early stages for effective treatment. In this paper, we propose an AD identification method using convolutional neural networks (CNNs) to assist doctors in diagnosis. Training CNN using the scores obtained from cognitive function tests makes the AD identification method robust to noisy labels. Through experiments using a large-scale database, we demonstrate the effectiveness of our proposed method. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | computer aided diagnosis / brain MRI image / Alzheimer’s disease / convolutional neural network |
| Paper # | MICT2021-31,MI2021-29 |
| Date of Issue | 2021-10-29 (MICT, MI) |
| Conference Information | |
| Committee | MI / MICT |
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| Conference Date | 2021/11/5(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Medical imaging technology, healthcare and medical information communication technology |
| Chair | Hidekata Hontani(Nagoya Inst. of Tech.) / Eisuke Hanada(Saga Univ.) |
| Vice Chair | Hideaki Haneishi(Chiba Univ.) / Takayuki Kitasaka(Aichi Inst. of Tech.) / Hirokazu Tanaka(Hiroshima City Univ.) / Daisuke Anzai(Nagoya Inst. of Tech.) |
| Secretary | Hideaki Haneishi(Yamaguchi Univ.) / Takayuki Kitasaka(Univ. of Hyogo) / Hirokazu Tanaka(Yokohama National Univ.) / Daisuke Anzai(KISTEC) |
| Assistant | Hotaka Takizawa(Tsukuba Univ.) / Yoshito Otake(NAIST) / Takahiro Ito(Hiroshima City Univ) / Kento Takabayashi(Okayama Pref. Univ.) / Takuya Nishikawa(National Cerebral and Cardiovascular Center Hospital) |
| Paper Information | |
| Registration To | Technical Committee on Medical Imaging / Technical Committee on Healthcare and Medical Information Communication Technology |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Performance Improvement of Alzheimer's Disease Identification Using Cognitive Function Test Scores |
| Sub Title (in English) | |
| Keyword(1) | computer aided diagnosis |
| Keyword(2) | brain MRI image |
| Keyword(3) | Alzheimer’s disease |
| Keyword(4) | convolutional neural network |
| 1st Author's Name | Daiki Endo |
| 1st Author's Affiliation | Tohoku University(Tohoku Univ.) |
| 2nd Author's Name | Koichi Ito |
| 2nd Author's Affiliation | Tohoku University(Tohoku Univ.) |
| 3rd Author's Name | Takafumi Aoki |
| 3rd Author's Affiliation | Tohoku University(Tohoku Univ.) |
| Date | 2021-11-05 |
| Paper # | MICT2021-31,MI2021-29 |
| Volume (vol) | vol.121 |
| Number (no) | MICT-230,MI-231 |
| Page | pp.pp.17-21(MICT), pp.17-21(MI), |
| #Pages | 5 |
| Date of Issue | 2021-10-29 (MICT, MI) |