WORC

This collection contains the WORC Database: imaging data, segmentations, and ground truth labels (e.g. diagnosis, phenotype, genetics) of 930 anonymized patients collected at the Erasmus Medical Center (Rotterdam, the Netherlands) with a variety of tumor types (e.g. liver, soft tissue, lung metastases) as published in the following two papers:

1) Starmans et al. "Reproducible radiomics through automated machine learning validated on twelve clinical applications", submitted, preprint available from https://arxiv.org/abs/2108.08618; and 2) Starmans et al. "The WORC* database: MRI and CT scans, segmentations, and clinical labels for 930 patients from six radiomics studies", submitted, preprint available from https://doi.org/10.1101/2021.08.19.21262238.

By downloading the data, you agree to the following Data Usage Policy:

The dataset is freely available under the following license: https://xnat.bmia.nl/data/projects/worc/resources/License/files/WORC_data_license.pdf. This license dictates among others that:

1) others can remix, adapt and build upon this work only non-commercially; 2) the data may not be redistributed. 3) when using (part of) this dataset, please cite the two above mentioned papers.

See the license for all conditions (https://xnat.bmia.nl/data/projects/worc/resources/License/files/WORC_data_license.pdf).

Code to download the data and reproduce the radiomics experiments as detailed in the above papers can be found at https://github.com/MStarmans91/WORCDatabase.

Data and Resources

This dataset has no data

Additional Info

Field Value
Title WORC
Description

This collection contains the WORC Database: imaging data, segmentations, and ground truth labels (e.g. diagnosis, phenotype, genetics) of 930 anonymized patients collected at the Erasmus Medical Center (Rotterdam, the Netherlands) with a variety of tumor types (e.g. liver, soft tissue, lung metastases) as published in the following two papers:

1) Starmans et al. "Reproducible radiomics through automated machine learning validated on twelve clinical applications", submitted, preprint available from https://arxiv.org/abs/2108.08618; and 2) Starmans et al. "The WORC* database: MRI and CT scans, segmentations, and clinical labels for 930 patients from six radiomics studies", submitted, preprint available from https://doi.org/10.1101/2021.08.19.21262238.

By downloading the data, you agree to the following Data Usage Policy:

The dataset is freely available under the following license: https://xnat.bmia.nl/data/projects/worc/resources/License/files/WORC_data_license.pdf. This license dictates among others that:

1) others can remix, adapt and build upon this work only non-commercially; 2) the data may not be redistributed. 3) when using (part of) this dataset, please cite the two above mentioned papers.

See the license for all conditions (https://xnat.bmia.nl/data/projects/worc/resources/License/files/WORC_data_license.pdf).

Code to download the data and reproduce the radiomics experiments as detailed in the above papers can be found at https://github.com/MStarmans91/WORCDatabase.

Keywords
Contact points
Contact point 1
URI
Name
Health-RI servicedesk
Name (translations)
Email
servicedesk@health-ri.nl
Identifier
http://example.com/
URL
Publisher
Publisher 1
URI
Name
Health-RI
Name (translations)
Email
URL
Type
Identifier
https://health-ri.nl
Creator
Creator 1
URI
Name
Dr. ir. Stefan Klein
Name (translations)
Email
URL
Type
Identifier
http://example.com
Creator 2
URI
Name
Dr. Martijn Starmans
Name (translations)
Email
URL
Type
Identifier
http://example.com
Landing page
Release date 2025-06-30T00:00:14+00:00
Modification date 2025-06-30T00:00:14+00:00
Temporal start date
Temporal end date
In Series
    Version
    Version notes
    Identifier https://xnat-acc.health-ri.nl/data/archive/projects/worc
    Frequency
    Provenance
    Type
    Temporal coverage
    Temporal resolution
    Spatial coverage
    Spatial resolution in meters
    Access rights
    Other identifier
    Theme
    1. http://publications.europa.eu/resource/authority/data-theme/HEAL
    Language
    1. http://id.loc.gov/vocabulary/iso639-1/en
    Documentation
    Conforms to
    Is referenced by
    Analytics
    Applicable legislation
    Has version
    Code values
    Coding system
    Purpose
    Health category
    Health theme
    Legal basis
    Minimum typical age
    Maximum typical age
    Number of records
    Number of records for unique individuals.
    Personal data
    Publisher note
    Publisher type
    Trusted Data Holder
    Population coverage
    Retention period
    Health data access body
    Qualified relation
    Provenance activity
    Qualified attribution
    Quality annotations
    URI https://fdp-acc.healthdata.nl/dataset/66b9c86c-c96a-45b1-b38b-481c6fbf84b7