| Literature DB >> 31470936 |
Abdalla Ibrahim1, Martin Vallières2, Henry Woodruff1, Sergey Primakov1, Mohsen Beheshti3, Simon Keek1, Turkey Refaee1, Sebastian Sanduleanu1, Sean Walsh1, Olivier Morin4, Philippe Lambin1, Roland Hustinx5, Felix M Mottaghy6.
Abstract
Radiomics - the high-throughput computation of quantitative image features extracted from medical imaging modalities- can be used to aid clinical decision support systems in order to build diagnostic, prognostic, and predictive models, which could ultimately improve personalized management based on individual characteristics. Various tools for radiomic features extraction are available, and the field gained a substantial scientific momentum for standardization and validation. Radiomics analysis of molecular imaging is expected to provide more comprehensive description of tissues than that of currently used parameters. We here review the workflow of radiomics, the challenges the field currently faces, and its potential for inclusion in clinical decision support systems to maximize disease characterization, and to improve clinical decision-making. We also present guidelines for standardization and implementation of radiomics in order to facilitate its transition to clinical use.Mesh:
Year: 2019 PMID: 31470936 DOI: 10.1053/j.semnuclmed.2019.06.005
Source DB: PubMed Journal: Semin Nucl Med ISSN: 0001-2998 Impact factor: 4.446