| Presentation | 2022-09-15 Automatic Multi-Measure Classification of Hip Osteoarthritis Based on Digitally-Reconstructed Radiographs using Deep Learning Masachika Masuda, Mazen Soufi, Yoshito Otake, Keisuke Uemura, Masaki Takao, Nobuhiko Sugano, Yoshinobu Sato, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Hip Osteoarthritis (HOA) is usually diagnosed by radiographs. In addition to the degree of cartilage degeneration, the degree of dislocation of the femoral head from the acetabulum (subluxation or dislocation) should also be evaluated. Recently, an automatic classification method using Convolutional Neural Networks (CNNs) has been reported; however, HOA diagnosis was addressed as a binary classification problem, therefore it was not able to represent clinically important changes in shape and intensity values with the disease progression. Therefore, the purpose of this study was to develop an automated HOA classification approach that incorporates information on disease progression based on Digitally-Reconstructed Radiographs (DRRs). The novelty is that it simultaneously classifies each DRR into two diagnostic measures, i.e., the Crowe classification (degree of dislocation) and the Kellgren-Lawrence score (OA severity), to represent clinically important changes. Three deep learning-based classifiers, i.e. VGG, DenseNet and ViT, were evaluated. The impact of involving dropout sampling at test-time for model uncertainty estimation was also evaluated. The ViT performance was superior to the other classifiers in terms of the two-measure classification accuracy. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Deep Learning / Hip Osteoarthritis / Uncertainty |
| Paper # | MI2022-49 |
| Date of Issue | 2022-09-08 (MI) |
| Conference Information | |
| Committee | MI |
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| Conference Date | 2022/9/15(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Hidekata Hontani(Nagoya Inst. of Tech.) |
| Vice Chair | Hideaki Haneishi(Chiba Univ.) / Takayuki Kitasaka(Aichi Inst. of Tech.) |
| Secretary | Hideaki Haneishi(Yamaguchi Univ.) / Takayuki Kitasaka(Univ. of Hyogo) |
| Assistant | Takeshi Hara(Gifu Univ.) / Yoshito Otake(NAIST) |
| Paper Information | |
| Registration To | Technical Committee on Medical Imaging |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Automatic Multi-Measure Classification of Hip Osteoarthritis Based on Digitally-Reconstructed Radiographs using Deep Learning |
| Sub Title (in English) | |
| Keyword(1) | Deep Learning |
| Keyword(2) | Hip Osteoarthritis |
| Keyword(3) | Uncertainty |
| 1st Author's Name | Masachika Masuda |
| 1st Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
| 2nd Author's Name | Mazen Soufi |
| 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 | Keisuke Uemura |
| 4th Author's Affiliation | Osaka University(Osaka Univ.) |
| 5th Author's Name | Masaki Takao |
| 5th Author's Affiliation | Ehime University(Ehime Univ.) |
| 6th Author's Name | Nobuhiko Sugano |
| 6th Author's Affiliation | Osaka University(Osaka Univ.) |
| 7th Author's Name | Yoshinobu Sato |
| 7th Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
| Date | 2022-09-15 |
| Paper # | MI2022-49 |
| Volume (vol) | vol.122 |
| Number (no) | MI-188 |
| Page | pp.pp.1-4(MI), |
| #Pages | 4 |
| Date of Issue | 2022-09-08 (MI) |