Submit Your Data

The following information describes the process for submitting new imaging datasets to The Cancer Imaging Archive (TCIA).  If you have utilized existing TCIA data and wish to publish your analyses you can find instructions for doing that here.

Requesting permission to publish a new dataset

The value of TCIA increases as we receive new data sharing proposals from the research community. We do not charge a fee for sharing your data through TCIA except in rare circumstances where proposals are extremely large.  TCIA is funded by the National Cancer Institute, therefore all applications must have relevance to cancer research.  Researchers are encouraged to submit an application to publish their data.  These applications will be reviewed with the following criteria in mind:

• How important is this data set to facilitating research reproducibility in this topic area?
• Does this dataset address a data gap for critical current research for a clinical need?
• Is this a novel/unique dataset compared to what’s already in TCIA?
• Is the dataset of a sufficient size/scale and demographic distribution to support scientific conclusions or hypothesis development?
• Does the dataset contain sufficient supporting data and documentation?
  • Supporting data examples: Patient demographics, medical history/comorbidities, treatment details, outcomes, or image analyses (i.e. labels for classifications or segmentations).
• If the dataset consists of an analysis of image based data, is it based on a biological hypothesis or other proposed discovery about the patho-physiological basis of cancer?

Applications are reviewed quarterly by the TCIA Advisory Group to assess their utility to the TCIA user community. Proposals which contain supporting non-image data (e.g. patient outcomes, training classifiers/labels, tumor segmentations) are highly preferred to those which lack these characteristics. The Advisory Group is composed of staff from the National Cancer Institute (NCI) who are experts in cancer imaging, informatics and related technologies.  The current membership includes:

• Janet Eary, Associate Director, NCI Cancer Imaging Program
• Lalitha Shankar, Branch Chief, NCI Cancer Imaging Program
• Irina A. Lubensky, Chief, NCI Cancer Diagnosis Program
• Krishnan Patel, Assistant Research Physician, Radiation Oncology Branch, Center for Cancer Research

If approved, submitting sites must sign our non-negotiable TCIA Data Submission Agreement before data collection is initiated.  No modifications to this agreement will be accepted.  Please also verify your institution has read our Data Usage Policies and Restrictions page and understands the licensing options we offer.  We no longer allow licenses that prevent commercial use.

Please note that, if your proposal is approved, TCIA staff will help submitters perform extensive de-identification before the data leaves your site. Please do not de-identify your data before contacting us.  In most cases, attempts to do so end up removing important information that will complicate downstream re-use.

It is also important to note that it usually takes a few months to complete the submission process for new datasets as we are perpetually working through a steady queue of incoming data submissions from sites around the world.  Submission times vary greatly depending on how large the dataset is, how well the data are organized and what your availability is to work with us on your submission.  In some circumstances we can adjust priorities to accommodate more aggressive deadlines, but this is not usually possible so we highly encourage researchers to plan ahead and start the data publication process well before you’re trying to publish a paper about it!

Request to Publish a New Collection on TCIA

Submission process overview

Once we have determined your data set is an appropriate fit for the archive we will initiate the submission process. A TCIA submission team will be assigned to provide all the required tools and guidance for sending your data. Our TCIA de-identification and curation process documentation provides extensive details about the process, but the major steps include:

1. We will help you perform an initial de-identification of your data before it leaves your site. Please do not de-identify your data before contacting us.
2. We will review your submitted data to ensure the data are fully de-identified and the content of the data aligns with your submission proposal. TCIA reserves the right to not publish a dataset if the submitter does not provide all data described in their proposal form.
3. We will work with you to create a dataset summary page to inform users how your data might be of use to them.  Please review our guidance on auxiliary information we like to provide to the user community where available.
4. We will publish the final data set, provide you with a citation and digital object identifier (DOI) for your dataset, and announce its availability on our mailing list and social media channels.

Track your data’s usage

After your dataset is available on TCIA you can view our Data Usage Statistics page to find out how often users search or download your data.  You can also use your dataset’s Digital Object Identifier (DOI) to track citations.

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.

In addition to publishing new TCIA datasets we encourage the community to publish analyses derived from existing TCIA datasets. Examples (see previously published analysis datasets) include image labels, annotations, organ/tumor segmentations, and radiomic/pathomic features.

Submitting a request to publish analysis results

Requests to publish analysis results on TCIA can be submitted by filling out this application form. Proposals will be reviewed with the following criteria in mind:

• How important is this data set to facilitating research reproducibility in this topic area?
• Does this dataset address a data gap for critical current research for a clinical need?
• Is this a novel/unique dataset compared to what’s already in TCIA?
• Is the dataset of a sufficient size/scale and demographic distribution to support scientific conclusions or hypothesis development?
• Does the dataset contain sufficient supporting data and documentation?
• Is the analysis based on a biological hypothesis or other proposed discovery about the patho-physiological basis of cancer?
• What is the biological relevance of segmentations/annotations/features?
• What scientific criteria were used to determine the methodology of image analysis?

Applications are reviewed quarterly by the TCIA Advisory Group to assess their utility to the TCIA user community.  The Advisory Group is composed of staff from the National Cancer Institute (NCI) who are experts in cancer imaging, informatics and related technologies.  The current membership includes:

• Janet Eary, Associate Director, NCI Cancer Imaging Program
• Lalitha Shankar, Branch Chief, NCI Cancer Imaging Program
• Irina A. Lubensky, Chief, NCI Cancer Diagnosis Program
• Krishnan Patel, Assistant Research Physician, Radiation Oncology Branch, Center for Cancer Research

If approved, submitting sites must sign our non-negotiable TCIA Data Submission Agreement before data collection is initiated.  No modifications to this agreement will be accepted.  Please also verify your institution has read our Data Usage Policies and Restrictions page and understands the licensing options we offer.  We no longer allow licenses that prevent commercial use.

Request to Publish Analysis Results on TCIA

Submission process overview

Once we have determined your data set is an appropriate fit for the archive we will initiate the submission process. A TCIA submission team will be assigned to provide all the required tools and guidance for sending your data. The major steps for publishing Analysis Results are as follows:

1. We will provide you with submission instructions and software tailored to your dataset.
2. If the images that you analyzed are in DICOM format, we highly recommend any image-derived data (such as annotations and image analysis results) are also published in DICOM format.  Conversion to DICOM SEG from NIfTI or NRRD formats can be done using publicly available, open-source tools (https://github.com/QIICR/dcmqi).  We are able to provide conversion assistance if you have any questions while using this tool.  Providing your analyses in DICOM format has the following benefits:
   1. Using DICOM enables you to include key metadata (e.g. orientation, relationship to original image UIDs) which reduces variability and inconsistencies during downstream usage of data.
   2. DICOM allows your data to be searchable on the TCIA Radiology Portal and through our API, making it more accessible and easier to find.
   3. DICOM datasets become available on NCI Imaging Data Commons, a publicly available cloud-based resource, providing greater visibility of your work.
   4. Popular open-source tools such as 3D Slicer and OHIF viewer (Open Health Imaging Foundation) support DICOM for annotations and segmentations.
3. We will review your submitted data to ensure the data are fully de-identified and the content of the data aligns with your submission proposal. TCIA reserves the right to not publish a dataset if the submitter does not provide all data described in their proposal form.
4. We will work with you to create a dataset summary page to inform users how your data might be of use to them.
5. We will publish the final data set, provide you with a data citation and digital object identifier (DOI), and announce its availability on our mailing list and social media channels.

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.