| Presentation | 2018-11-05 [Poster Presentation] Posterior mean approximation solution combining multiple image prior distributions in MR image reconstruction Nanako Kubota, Ken Harada, Koji Fujimoto, Tomohisa Okada, Masato Inoue, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In the MR image reconstruction, combining multiple image prior distributions is preferred to obtain better results, but finding the optimal combination of prior weights by the cross-validation method is difficult because the number of combinations increases exponentially w.r.t. the number of priors. In this manuscript, we solve this problem by the ensemble learning. Furthermore, we give meaning to this solution as an approximate of the posterior mean. As a result, the accuracy (mean square error) of reconstructed images was improved without increasing the order of the calculation cost. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | MR image reconstruction / compressed censing / posterior mean estimate / ensemble learning |
| Paper # | IBISML2018-47 |
| Date of Issue | 2018-10-29 (IBISML) |
| Conference Information | |
| Committee | IBISML |
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| Conference Date | 2018/11/5(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hokkaido Citizens Activites Center (Kaderu 2.7) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Information-Based Induction Science Workshop (IBIS2018) |
| Chair | Hisashi Kashima(Kyoto Univ.) |
| Vice Chair | Masashi Sugiyama(Univ. of Tokyo) / Koji Tsuda(Univ. of Tokyo) |
| Secretary | Masashi Sugiyama(Nagoya Inst. of Tech.) / Koji Tsuda(AIST) |
| Assistant | Tomoharu Iwata(NTT) / Shigeyuki Oba(Kyoto Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Infomation-Based Induction Sciences and Machine Learning |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Poster Presentation] Posterior mean approximation solution combining multiple image prior distributions in MR image reconstruction |
| Sub Title (in English) | |
| Keyword(1) | MR image reconstruction |
| Keyword(2) | compressed censing |
| Keyword(3) | posterior mean estimate |
| Keyword(4) | ensemble learning |
| 1st Author's Name | Nanako Kubota |
| 1st Author's Affiliation | Waseda University(Waseda Univ.) |
| 2nd Author's Name | Ken Harada |
| 2nd Author's Affiliation | Waseda University(Waseda Univ.) |
| 3rd Author's Name | Koji Fujimoto |
| 3rd Author's Affiliation | Kyoto University(Kyoto Univ.) |
| 4th Author's Name | Tomohisa Okada |
| 4th Author's Affiliation | Kyoto University(Kyoto Univ.) |
| 5th Author's Name | Masato Inoue |
| 5th Author's Affiliation | Waseda University(Waseda Univ.) |
| Date | 2018-11-05 |
| Paper # | IBISML2018-47 |
| Volume (vol) | vol.118 |
| Number (no) | IBISML-284 |
| Page | pp.pp.23-28(IBISML), |
| #Pages | 6 |
| Date of Issue | 2018-10-29 (IBISML) |