| Presentation | 2019-05-17 Personalized head models from MRI using convolutional neural networks Essam Rashed, Jose Gomez-Tames, Akimasa Hirata, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Transcranial magnetic stimulation (TMS) is a non-invasive clinical technique used for treatment of several neurological diseases. The brain induced electric field is known for inter- /intra- subject variabilities, which make it difficult to accurately adjust TMS parameters for different subjects. Therefore, a computer simulation is frequently used to simulate different TMS setups using models generated from anatomical images (e.g. MRI) of the examined subject. Human head models are generated by segmentation of MRI images into different anatomical tissues with isotropic electric conductivity each. This process is time-consuming and requires a special experience to segment a relatively large number of tissues. In this paper, we propose a deep convolution neural network for human head segmentation that is convenient for simulation of electrical field distribution, such as TMS. The proposed network is used to generate personalized head models from MRI with high accuracy. Results indicate that the personalized head models generated using the proposed method demonstrate strong matching with those achieved from manually segmented ones. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Convolutional neural networkdeep learningimage segmentationtranscranial magnetic stimulation |
| Paper # | EST2019-3 |
| Date of Issue | 2019-05-10 (EST) |
| Conference Information | |
| Committee | EST |
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| Conference Date | 2019/5/17(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nagoya Inst. Tech. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Simulation techniques, etc. |
| Chair | Akimasa Hirata(Nagoya Inst. of Tech.) |
| Vice Chair | Shinichiro Ohnuki(Nihon Univ.) / Masayuki Kimishima(Advantest) / Jun Shibayama(Hosei Univ.) |
| Secretary | Shinichiro Ohnuki(CIST) / Masayuki Kimishima(National Inst. of Tech.,Sendai College) / Jun Shibayama |
| Assistant | Takahiro Ito(Nagoya Inst. of Tech.) / Kazuhiro Fujita(Fujitsu) |
| Paper Information | |
| Registration To | Technical Committee on Electronics Simulation Technology |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Personalized head models from MRI using convolutional neural networks |
| Sub Title (in English) | |
| Keyword(1) | Convolutional neural networkdeep learningimage segmentationtranscranial magnetic stimulation |
| 1st Author's Name | Essam Rashed |
| 1st Author's Affiliation | Nagoya Institute of Technology(NITech) |
| 2nd Author's Name | Jose Gomez-Tames |
| 2nd Author's Affiliation | Nagoya Institute of Technology(NITech) |
| 3rd Author's Name | Akimasa Hirata |
| 3rd Author's Affiliation | Nagoya Institute of Technology(NITech) |
| Date | 2019-05-17 |
| Paper # | EST2019-3 |
| Volume (vol) | vol.119 |
| Number (no) | EST-42 |
| Page | pp.pp.9-12(EST), |
| #Pages | 4 |
| Date of Issue | 2019-05-10 (EST) |