| Presentation | 2022-11-18 Extrapolation of partial X-ray image for prediction of whole body musculoskeletal structure Weiqi Zhang, Yi Gu, Yoshito Otake, Soufi Mazen, Keisuke Uemura, Masaki Takao, Toshiaki Akashi, Kensaku Mori, Kento Aida, Nobuhiko Sugano, Yoshinobu Sato, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Image defects and partial disorders are common problems in medical imaging. Image inpainting and extrapolation are helpful techniques to restore missing image information for many clinical applications, including analyzing organs or tissues that are not scanned during imaging processing. Many image restoration algorithms have been proposed for general images. However, numerous challenges still exist in restoring medical images, such as domain shifting and limited datasets. Conventional methods for medical image restoration only focused on recovering small regions within a given image, ignoring clinical demands for extrapolation. In this study, we proposed a method based on the transformer for restoring an X-ray image with large regions, which supports whole-body restoration from a partial region, using mutual conversion between an X-ray image and a digitally reconstructed radiograph. Our method combined an extrapolation network and a style transfer network, simultaneously achieving the inpainting and extrapolating of an X-ray image under a limited dataset. To the best of our knowledge, we are the first to achieve whole-body restoration from an X-ray image. We conducted 1) quantitative and qualitative experiments on the extrapolation and style transfer models and 2) bone mineral density (BMD) estimation experiments from extrapolated X-ray images generated by the proposed method. We used the predicted and ground-truth BMD correlation to evaluate our model's effectiveness, which achieved PCC of 0.374 and 0.534 in DXA-measured and QCT-measured BMD, respectively, demonstrating the high clinical potential of analyzing missing regions using the proposed method. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Image Extrapolation / X-ray Image / Transformer / Bone Mineral Density (BMD) Estimation |
| Paper # | MICT2022-38,MI2022-67 |
| Date of Issue | 2022-11-11 (MICT, MI) |
| Conference Information | |
| Committee | MICT / MI |
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| Conference Date | 2022/11/18(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nagoya Institute of Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Medical imaging technology, healthcare and medical information communication technology, etc. |
| Chair | Hirokazu Tanaka(Hiroshima City Univ.) / Hidekata Hontani(Nagoya Inst. of Tech.) |
| Vice Chair | Chika Sugimoto(Yokohama National Univ.) / Daisuke Anzai(Nagoya Inst. of Tech.) / Hideaki Haneishi(Chiba Univ.) / Takayuki Kitasaka(Aichi Inst. of Tech.) |
| Secretary | Chika Sugimoto(Okayama Pref. Univ.) / Daisuke Anzai(KISTEC) / Hideaki Haneishi(Yamaguchi Univ.) / Takayuki Kitasaka(Univ. of Hyogo) |
| Assistant | Takahiro Ito(Hiroshima City Univ) / Natsuki Nakayama(Nagoya Univ.) / Takuya Nishikawa(National Cerebral and Cardiovascular Center Hospital) / Takeshi Hara(Gifu Univ.) / Yoshito Otake(NAIST) |
| Paper Information | |
| Registration To | Technical Committee on Healthcare and Medical Information Communication Technology / Technical Committee on Medical Imaging |
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| Language | ENG-JTITLE |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Extrapolation of partial X-ray image for prediction of whole body musculoskeletal structure |
| Sub Title (in English) | |
| Keyword(1) | Image Extrapolation |
| Keyword(2) | X-ray Image |
| Keyword(3) | Transformer |
| Keyword(4) | Bone Mineral Density (BMD) Estimation |
| 1st Author's Name | Weiqi Zhang |
| 1st Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
| 2nd Author's Name | Yi Gu |
| 2nd Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
| 3rd Author's Name | Yoshito Otake |
| 3rd Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
| 4th Author's Name | Soufi Mazen |
| 4th Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
| 5th Author's Name | Keisuke Uemura |
| 5th Author's Affiliation | Osaka University(Osaka Univ) |
| 6th Author's Name | Masaki Takao |
| 6th Author's Affiliation | Ehime University(Ehime Univ) |
| 7th Author's Name | Toshiaki Akashi |
| 7th Author's Affiliation | Juntendo University(Juntendo Univ) |
| 8th Author's Name | Kensaku Mori |
| 8th Author's Affiliation | Nagoya University/National Institute of Informatics(Nagoya Univ/NII) |
| 9th Author's Name | Kento Aida |
| 9th Author's Affiliation | National Institute of Informatics(NII) |
| 10th Author's Name | Nobuhiko Sugano |
| 10th Author's Affiliation | Osaka University(Osaka Univ) |
| 11th Author's Name | Yoshinobu Sato |
| 11th Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
| Date | 2022-11-18 |
| Paper # | MICT2022-38,MI2022-67 |
| Volume (vol) | vol.122 |
| Number (no) | MICT-264,MI-265 |
| Page | pp.pp.24-28(MICT), pp.24-28(MI), |
| #Pages | 5 |
| Date of Issue | 2022-11-11 (MICT, MI) |