1.
Stud Health Technol Inform
; 270: 1319-1320, 2020 Jun 16.
Artigo
em Inglês
| MEDLINE
| ID: mdl-32570638
2.
Stud Health Technol Inform
; 247: 855-859, 2018.
Artigo
em Inglês
| MEDLINE
| ID: mdl-29678082
RESUMO
Performing image feature extraction in radiation oncology is often dependent on the organ and tumor delineations provided by clinical staff. These delineation names are free text DICOM metadata fields resulting in undefined information, which requires effort to use in large-scale image feature extraction efforts. In this work we present a scale-able solution to overcome these naming convention challenges with a REST service using Semantic Web technology to convert this information to linked data. As a proof of concept an open source software is used to compute radiation oncology image features. The results of this work can be found in a public Bitbucket repository.