| Literature DB >> 33170144 |
Matjaz Vogrin1,2, Teodor Trojner1, Robi Kelc1,2.
Abstract
Background Due to the rarity of primary bone tumors, precise radiologic diagnosis often requires an experienced musculoskeletal radiologist. In order to make the diagnosis more precise and to prevent the overlooking of potentially dangerous conditions, artificial intelligence has been continuously incorporated into medical practice in recent decades. This paper reviews some of the most promising systems developed, including those for diagnosis of primary and secondary bone tumors, breast, lung and colon neoplasms. Conclusions Although there is still a shortage of long-term studies confirming its benefits, there is probably a considerable potential for further development of computer-based expert systems aiming at a more efficient diagnosis of bone and soft tissue tumors.Keywords: artificial intelligence; cancer imaging; deep learning; image segmentation; tumor recognition
Year: 2020 PMID: 33170144 DOI: 10.2478/raon-2020-0068
Source DB: PubMed Journal: Radiol Oncol ISSN: 1318-2099 Impact factor: 2.991