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FAIR‐compliant clinical, radiomics and DICOM metadata of RIDER, interobserver, Lung1 and head‐Neck1 TCIA collections
Author(s) -
Kalendralis Petros,
Shi Zhenwei,
Traverso Alberto,
Choudhury Ananya,
Sloep Matthijs,
Zhovannik Ivan,
Starmans Martijn P.A.,
Grittner Detlef,
Feltens Peter,
Monshouwer Rene,
Klein Stefan,
Fijten Rianne,
Aerts Hugo,
Dekker Andre,
Soest Johan,
Wee Leonard
Publication year - 2020
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.14322
Subject(s) - dicom , metadata , head (geology) , cancer imaging , medical physics , radiomics , computer science , medical imaging , medicine , computer graphics (images) , artificial intelligence , world wide web , cancer , geology , geomorphology
One of the most frequently cited radiomics investigations showed that features automatically extracted from routine clinical images could be used in prognostic modeling. These images have been made publicly accessible via The Cancer Imaging Archive (TCIA). There have been numerous requests for additional explanatory metadata on the following datasets - RIDER, Interobserver, Lung1, and Head-Neck1. To support repeatability, reproducibility, generalizability, and transparency in radiomics research, we publish the subjects' clinical data, extracted radiomics features, and digital imaging and communications in medicine (DICOM) headers of these four datasets with descriptive metadata, in order to be more compliant with findable, accessible, interoperable, and reusable (FAIR) data management principles.