In addition to publishing new TCIA datasets we encourage the community to publish analyses derived from existing TCIA datasets. Examples (see previously uploaded analysis datasets) include image labels, annotations, organ/tumor segmentations, and radiomic/pathomic features.
Submitting a request to publish analysis results
Requests to share analysis results on TCIA can be submitted by filling out this application form. Proposals will be reviewed on a monthly basis by the TCIA Advisory Group using the following criteria:
- How will other researchers benefit if we add your data to TCIA?
- What scientific criteria was used to determine the methodology of segmentation/annotation/features?
- What is the biological relevance of segmentations/annotations/features?
TCIA highly recommends submissions of imaging and image-derived data (such as annotations and image analysis results) in DICOM format which preserves crucial metadata, for the following reasons:
- Using DICOM enables you to include key metadata necessary for easy re-use by others. The inclusion of metadata also limits variability due to different image processing tools. Failure to use DICOM data during submission might also lead to further inconsistencies during downstream usage of data.
- Popular open-source tools such as 3D Slicer and OHIF viewer (Open Health Imaging Foundation) support DICOM for annotations and segmentations.
- Allows your data to be searchable on the TCIA Radiology Portal and through our API.
- DICOM collections become available on NCI Imaging Data Commons, a publicly available cloud-based resource, providing greater visibility.
Conversion to DICOM SEG from NIfTI or NRRD formats can be done using publicly available, open-source tools (https://github.com/QIICR/dcmqi,https://github.com/herrmannlab/highdicom)
If accepted, your proposal will be prioritized and assigned to one of our curation teams who will assist you through the submission process. Your data will be published with a citation and corresponding digital object identifier (DOI) which can be cited in publications. To help other users find your dataset on TCIA entries will be added on the Collection pages of any TCIA dataset your analyses utilized, and also to our Analysis Results directory page.
Getting credit for data sharing
New journals dedicated to describing data sets are beginning to gain in popularity. These can be used to publish detailed descriptions of your TCIA data to gain academic credit (publication/citations) for your efforts in addition to the novel scientific findings you might publish in traditional journals. Below is a list of data journals which recognize TCIA as a Recommended Repository.