Automated detection of pediatric forearm fractures in X-ray images using deep learning.
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| Title: | Automated detection of pediatric forearm fractures in X-ray images using deep learning. |
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| Authors: | Suzuki H; Graduate School of Science and Technology, Meijo University, 1-501 Shiogamaguchi, Tempaku-ku, Nagoya, 468-8502, Aichi, Japan., Teramoto A; Graduate School of Science and Technology, Meijo University, 1-501 Shiogamaguchi, Tempaku-ku, Nagoya, 468-8502, Aichi, Japan. teramoto@meijo-u.ac.jp., Honmoto T; Ibaraki Children's Hospital, 3-3-1 Futabadai, Mito, 311-4145, Ibaraki, Japan., Niki A; Ibaraki Children's Hospital, 3-3-1 Futabadai, Mito, 311-4145, Ibaraki, Japan., Kono T; Department of Radiology, Tokyo Metropolitan Children's Medical Center, 2-8-29,Musashidai, Tokyo, 183-8561, Fuchu, Japan., Fujita H; Faculty of Engineering, Gifu University, 1-1,Yanagido, Gifu, 501-1194, Japan. |
| Source: | Radiological physics and technology [Radiol Phys Technol] 2026 Jun; Vol. 19 (2), pp. 830-841. Date of Electronic Publication: 2026 May 06. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Japan Country of Publication: Japan NLM ID: 101467995 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1865-0341 (Electronic) Linking ISSN: 18650333 NLM ISO Abbreviation: Radiol Phys Technol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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