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Osteologie 2021; 30(03): 261-263
DOI: 10.1055/a-1534-3346
DOI: 10.1055/a-1534-3346
Gesellschaftsnachrichten
Informationen der Arbeitsgemeinschaft Knochentumoren e.
V.
Artificial Intelligence (AI) for Radiological Diagnostics of Bone Tumors: Potential Approaches, Possibilities, and Limitations
Publication History
Article published online:
17 September 2021
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- 1 Choy G, Khalilzadeh O, Michalski M. et al. Current Applications and Future Impact of Machine Learning in Radiology. Radiology 2018; 288: 318-328
- 2 Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology 2016; 278: 563-577
- 3 Fletcher CDM. WHO Classification of Tumours of Soft Tissue and Bone; 4th ed.: World Health Organization; 2013
- 4 Paszke A, Gross S, Chintala S et al. Automatic differentiation in PyTorch. In: NIPS-W; 2017
- 5 Lalam R, Bloem JL, Noebauer-Huhmann IM. et al. ESSR Consensus Document for Detection, Characterization, and Referral Pathway for Tumors and Tumorlike Lesions of Bone. Seminars in musculoskeletal radiology. 2017; 21: 630-647