| Literature DB >> 30248184 |
Thomas R Mackie1, Edward F Jackson1, Maryellen Giger2.
Abstract
BACKGROUND: This article is a summary of the quantitative imaging subgroup of the 2017 AAPM Practical Big Data Workshop (PBDW-2017) on progress and challenges in big data applied to cancer treatment and research supplemented by a draft white paper following an American Association of Physicists in Medicine FOREM meeting on Imaging Genomics in 2014. AIMS: The goal of PBDW-2017 was to close the gap between theoretical vision and practical experience with encountering and solving challenges in curating and analyzing data.Entities:
Keywords: big data; deep learning; imaging biomarkers; quantitative imaging; radiomics
Mesh:
Year: 2018 PMID: 30248184 DOI: 10.1002/mp.13135
Source DB: PubMed Journal: Med Phys ISSN: 0094-2405 Impact factor: 4.071