Automated scoliosis X-ray cobb angle classification: a deep learning approach with RadImageNet.
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| Title: | Automated scoliosis X-ray cobb angle classification: a deep learning approach with RadImageNet. |
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| Authors: | Yu J; Icahn School of Medicine at Mount Sinai, New York, USA. jennifer.yu@icahn.mssm.edu., Lahoti Y; Icahn School of Medicine at Mount Sinai, New York, USA., Ahmed H; Icahn School of Medicine at Mount Sinai, New York, USA., Kurapatti M; Icahn School of Medicine at Mount Sinai, New York, USA., Frost J; Icahn School of Medicine at Mount Sinai, New York, USA., Song J; Icahn School of Medicine at Mount Sinai, New York, USA., Corvi J; Icahn School of Medicine at Mount Sinai, New York, USA., Namiri N; Icahn School of Medicine at Mount Sinai, New York, USA., Issa T; Icahn School of Medicine at Mount Sinai, New York, USA., Cho S; Icahn School of Medicine at Mount Sinai, New York, USA., Kim J; Icahn School of Medicine at Mount Sinai, New York, USA. |
| Source: | European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society [Eur Spine J] 2026 Jul 09. Date of Electronic Publication: 2026 Jul 09. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 9301980 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-0932 (Electronic) Linking ISSN: 09406719 NLM ISO Abbreviation: Eur Spine J Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1432-0932 |
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| DOI: | 10.1007/s00586-026-10181-2 |
