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  1. to assess existing software and instantiations that are appropriate to their research or clinical needs.
  2. to locate relevant  publicly available data for research

Publicly Hosted Biomedical Imaging Archives

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NBIA

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NIAMS

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Central XNAT

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Image Data Archive

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BIRN Data Repository

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NIRL Imaging Database

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Give A Scan

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Optical Society of America (OSA)

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Pediatric MRI Data Repository

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Sponsor(s)

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Cancer Imaging Program, caBIG

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NIAMS, caBIG

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BIRN

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Lab of NeuroImaging UCLA (LONI)

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BIRN

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BIRN

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Lung Cancer Alliance

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Optical Society of America

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NDAR

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Content Type

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In Vivo Cancer Imaging

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Osteoarthritis

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Osteoarthritis

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ADNI (Alzheimers),
CRYO (histology),
ICBM (Brain mapping),
AIBL (Autralian Aging)

...

Alzheimer's Medical Imaging

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ELUDE (Elderly Depression),
MIRIAD (Depression)

...

Patient-contributed Medical scans

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Autism Research

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Autism

We encourage any feedback from the wider community that may help improve this information or correct any misconceptions stated below. The survey is divided into two sections:

  1. Publicly hosted biomedical imaging archives which are populated with actual data which researchers, teachers, industry, etc may wish to utilize
  2. Image archive software solutions which one could download and use to host their own DICOM image data sets

Please contact Justin Kirby (kirbyju@mail.nih.gov) or John Freymann (freymanj@mail.nih.gov) with any questions, error reports, updates, additions, etc. 

Acknowledgements

We would like to thank the following people for volunteering their time and effort in helping us populate this survey.

  • Dan Marcus (WUSTL)
  • Brian Hughes (Terpsys)
  • Dan Hall (NIH)
  • Patrick Reynolds (Kitware)
  • Julien Jomier (Kitware)
  • Ivo Dinov (UCLA)
  • Matthew McAuliffe (NIH)
  • David Keator (UCI)
  • Christian Haselgrove (NITRC)

Publicly Hosted Biomedical Imaging Archives

The following table attempts to summarize publicly accessible biomedical image archives.  This survey originally initiated in August of 2010.  Information in the tables are being updated periodically.  

NOTE: Due to the large size of this table you may need to use the horizontal scroll bar at the bottom of the table to view some of the archives listed furthest to the right.

 

The Cancer Imaging Archive (TCIA)

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NBIA

NIAMS

XNAT Central

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Image Data Archive

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Function BIRN Data Repository

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Give A Scan

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Optical Society of America (OSA)

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Insight Journal (MIDAS)

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National Database for Autism Research (NDAR)

Pediatric MRI Data RepositoryFITBIRNITRC-IR
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Supporting Institution(s)

NCI Cancer Imaging Program

NCI Center for Bioinformatics and Information Technology

NIAMS, NCI Center for Bioinformatics and Information Technology

WUSTL, BIRN

Lab of NeuroImaging UCLA (LONI)

FBIRN Institutions

Lung Cancer Alliance, Kitware

Optical Society of America, Kitware

Kitware, Insight Software Consortium

NIH, NIMH, NINDS, NICHD, NIEHS

NIH, NIMH, NICHD, NIDA, NINDSNINDS, DoDNIH Blueprint, NIBIB, NINDS, NIMH, NIDA

Content Type

In Vivo Cancer Imaging, phantom imaging and related metada (see full Collection list)

Demo instance for showing the latest features of NBIA.  All data are re-used from The Cancer Imaging Archive.

Osteoarthritis

Biomedical images, meta data, other phenotypic data (behavioral, clinical, etc)

ADNI (Alzheimers),
CRYO (histology),
ICBM (Brain mapping),
AIBL (Autralian Aging)

FMRI/MRI images, behavioral data, and clinical data from schizophrenics and healthy volunteers.  Willing to accept data on other neurological disorders.

 

Patient-contributed Lung Cancer Medical scans

Optical, digital holography, 2D/3D modalities, etc

Biomedical images, meta data, and journal articles

Autism - standard phenotypic data, imaging and genomic/pedigree data related to human subjects

Normal brain development

 

TBI related data: imaging, phenotypic and some genomics; human but expanding to preclinical modelsNeuroimages

Archive Software

NBIA, AIM Data Service (XML image metadata), and a Clinical Data relational database

NBIA

NBIA

XNAT

Image Data Archive

Human Imaging Database (HID)

MIDAS

MIDAS

MIDAS

customSame as NDAR (custom)Biomedical Research Informatics Computing System (BRICS) NIH developed – customXNAT

Login account required

No.  Public data is accessible without logging in.  Some special restricted-access data sets do require free registration. Register on the TCIA website.

For advanced site features or limited access data sets, but is not required for accessing public data. Click here to register.

Yes. Register on the NIAMS website.

For accessing limited access data sets, but not for public data

Yes, via web https://ida.loni.ucla.edu/login.jsp
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No (email requested)

No

For accessing limited access data sets, but not for public data

Only for submitting data.

Yes

YesYesFor accessing limited access data sets, but not for public data

Explicit data sharing policy

Yes

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, with options for uploading fully open or limited access data sets

Yes, with options for uploading fully open or limited access data sets

Yes, found here

No, data is made public or restricted as specified by the user who uploads it.

Yes. IDA User Manual.

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All data is made publicly accessible.

All data is made publicly accessible.

Yes, found here

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All data is made publicly accessible (varying licenses)

Yes, found here

Similar to NDAR but there is no explicit policyYes, https://fitbir.nih.gov/jsp/about/policy.jspNo

Number of Registered Users (or NA)

6,117

2,712

46

~1,000

>1,000

N/A

N/A

 

2,657

60 for data access
100-200 for data submission

~30

15 – just starting

1976 users as of April, 2015

Accepting new data

Yes, proposals are accepted via email and reviewed monthly by the TCIA Advisory Committee. Acceptance criteria is summarized here: Requesting Permission to Upload your Data

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No

More data is being added as part of the official initiative, but external proposals are not being accepted.

Yes, users can register accounts and upload data

Yes, see section 9 in the Appendix of the LONI Policies & Procedures

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Yes, https://www.birncommunity.org/about/contact/

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Yes, through Lung Cancer Alliance. Learn more here

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Yes, new data may be added as part of future Optical Society of America publications are released.

Yes, users can register accounts and upload data.

Yes, learn more here

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NoYes, FITBIR has established a two-tiered submission strategy to ensure high quality and to provide maximum benefit to investigators.  See the Data Submission Procedures for more information.Yes.  Community-generated data sets may be suggested for inclusion.  Contact moderator@nitrc.org.

Central curation/review

Yes, a multiple tiered de-identification and QC process is utilized involving both human review and systematic analysis. The process is summarized in detail on the TCIA De-Identification Knowledge Base and What to Expect as an Image Provider

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No

Yes, performed by NIAMS staff.

No

Collaborators strip all personal info from data prior to submission to LONI. Then LONI auto filters again, to ensure that there are no PHI in the files (especially if the data is binary) and stores the data in quarantine, until it’s approved for posting to the web interface.

PHI must be removed by the submitting institution prior to giving the data to the FBIRN.

FBIRN also performs a review to make sure there aren't any de-identification problems.

Yes, performed by Lung Cancer Alliance

Yes, performed by the Optical Society of America

Yes, some QC performed by Kitware staff and peer reviews.  Most data is de-identified by the submitter prior to upload.

Sites do their own de-identification any way they prefer, so long as it meets their IRB's approval. 

Pre-validation is performed to ensure all data conforms/harmonizes to the autism data dictionary. QA is also performed by NDAR staff to check for identifiable information.

Archived project, no longer receiving new data.Yes, pre-validation is performed to ensure all data conforms to the NINDS CDEs. QA is also performed by staff to check for personal identifiable information.Yes, performed by NITRC.

Availability/Uptime

~99%, hosted on a redundant production system at WUSTL

~99%, hosted on a redundant production system at NCI CBIIT

~99%, hosted on a redundant production system at NCI CBIIT

~99%

Continuous (no exact % specified)

Continuous (no exact % specified)

~99.9%, hosted on a production server at Kitware

~99.9%, hosted on a production server at OSA

~99%, hosted on a production server at Kitware

~99%, imaging data hosted on Amazon and metadata hosted by NIH.

~99%, hosted by NIH.~99%, hosted by NIH.~99.9%, hosted on production servers at UCSD.

Project- or Collection- based groupings?

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

NoYesYes

Size of Current Volume

TCIA: 2.26 TB

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NLST-LSS: 6.5 TB
NLST-ACRIN: 4.8 TB
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Total: 13.56 TB

~21GB

~7.5TB

1 TB

0.7 PB

~2TB

33GB

~50GB

~60GB

~2TB

~2TB0.5TB1.5 TB

Number of patients/subjects with imaging

TCIA: 5,997

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NLST-LSS: 17,043
NLST-ACRIN: 9,211
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Total: 32,251

32

4,796

3,494

> 120,000

~300

37

N/A

> 200, plus some non-patient data

2500 NDAR

 

550 (migrated into NDAR)2006854 subjects

Number of DICOM Tags query-able

2 via the Simple Search, ~90 via the Advanced Search, and all DICOM metadata can be queried using the Text Search option.

2 via the Simple Search, ~90 via the Advanced Search, and all DICOM metadata can be queried using the Text Search option.

~90

~50

50

0

22 (imaging parameters in query interface)

N/A

22 (imaging parameters in query interface)

9, with full listing from data dictionary. (4 NDAR, 5 Pediatric MRI)

9, with full listing from data dictionary. (4 NDAR, 5 Pediatric MRI)10N/A
Metadata AvailabilityWide variety of clinical, genetic, and image segmentation/annotation available is available for various data sets.  Full summary can be viewed here
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in the "Supporting Data Available" column.
NoneNone

Various clinical and other metadata

Biospecimen, clinical, pathological, neuropsychiatric, and demographic.Yes, extensive behavioral data and clinical data. 

Some unstructured clinical data such as patient age, cancer stage, recurrence, and treatment information.

Associated articles, figures, publication-specific metadata, etcUnstructured clinical data as well as publication-specific metadata

NDAR contains all human subjects data related to autism research funded by the NIH and others.  Outside of the NDAR data dictionary, Metadata supporting project definition and research results are provided (see data from papers). 

 

 

Yes, all metadata is collected using NINDS CDEs

Gender, age, handedness, diagnosis, and MR acquisition parameters. Various cognitive assessments and other rich metadata available for some data.

Data submission/download methods

Submission via DICOM or HTTPS protocols using CTP

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. Download via Java Webstart client. A REST API is also available with documentation.

Submission via DICOM or HTTPS protocols using CTP

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. Download via Web (zip), FTP, Java Webstart client

Submission via DICOM or HTTPS protocols using CTP

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. Download via Web (zip), FTP, Java Webstart client

Submission via Web UI or DICOM protocol.  Download via Web (zip) or Java applet.

Secure web upload

Downloads via Web UI, Submissions via https://www.birncommunity.org/about/contact/

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Submission via Web UI,
Download via Web (zip).

Submission via Web UI,
Download via Web (zip).

Submission via Web UI, DICOM push, MIDASDesktop.


Download via Web (zip), MIDASDesktop

A custom Java Webstart application allows SFTP/Amazon S3 transfers.  MIPAV is offered as an optional method for de-identification.  Submission is harmonized to the autism data standard using custom data validation software. 

Download methods include multithreaded download from the Amazon Cloud or push to cloud computational pipeline.

Not applicable.They can use MIPAV for submitting images. Submissions must conform to FITBIR Data Dictionary (NINDS CDEs). A custom Java Webstart application allows SFTP transfers.Upload by arrangement.  Download via Web (zip), Java applet, or REST API.

Helpdesk Support

Yes, the TCIA Helpdesk 

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supports both end users and submitters. They provide phone and email support during regular business hours Mon-Fri.

Yes, CBIIT Application Support

Yes, CBIIT Application Support

Via XNAT discussion group

dba@loni.ucla.edu

Yes, via https://www.birncommunity.org/about/contact/

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Technical issues can be sent to midas@public.kitware.com or click here for  Administrative support and other questions

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Contact infobase@osa.org.

Contact midas@public.kitware.com

Yes, available at ndarhelp@mail.nih.gov.

Yes, pedsmri@mail.nih.gov.Yes, FITBIR-help@mail.nih.govContact moderator@nitrc.org.

Affiliation with Journal

Not directly, but Digital Object Identifiers can be provided for integration with publications.  TCIA is also a recommended repository for Nature's Scientific Data journal.

No

No

No

Yes, NeuroImage

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No

No

Yes, Optics Info Base

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Yes, Insight Journal

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No

NoNoNo

Intended Audience(s)

Cancer researchers, engineers and developers, professors

Anyone interested in testing the functionality of the NBIA software.

Osteoarthritis researchers

All imaging research

Neuroimaging and genetics research

Neuroimaging research

Lung cancer researchers

Optical Society of America subscribers

All imaging research

Autism researchers (clinical/phenotype/genomic), both those receiving autism related NIH grants and other investigators sponsored by an NIH recognized institution with a current federal-wide assurance.

Neuroscientists interested in normative brain study of child development.TBI researchersNeuroimaging research


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Image archive software solutions

Below is a list of image archive solutions that can be deployed by interested parties wishing to build their own DICOM based biomedical image archive. This list omits some of the archives above in cases where we could not find any information about how one might download and deploy their own instance of the software.

Software Name and Web Site

NBIA GForge project

XNAT

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MIDAS

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Interface/GUI

Web

Web

Web/Desktop Application

Query types/flexibility

Simple (9 parameters), Advanced (10 more parameters), Dynamic (boolean query of up to 90 DICOM tags)

Extensible set of DICOM tags as well as linked quantitative biomarkers, linked clinical data, and other non-imaging data.

Customizable, search by any tags registered in the system

Role Based Security

Yes

Yes

Yes

Public access option (no login req)

Yes

Yes

Yes

Active Development

Yes, NCI CBIIT

Yes, WUSTL Neuroinformatics Research Group

Yes, Kitware

License

Open source - NBIA License Agreement Details

Non-restrictive (BSD) open-source license - XNAT License Agreement Details

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non-restrictive (BSD) open-source license

API available

Yes, REST

Yes, REST

Yes, REST, OAI-PMH

Supported image formats

DICOM

Automated import of DICOM and ECAT. Custom importers can be implemented for other formats.  Any file type can be uploaded through the API and web interface.

DICOM and other ITK-based format

Supported metadata formats

XML, Zip

XML, CSV. Custom data import logic can be implemented via pluggable Groovy and Python scripts.

XML

Transfer protocols (import/export)

DICOM, HTTPS

DICOM, HTTPS

DICOM, HTTPS

Controlled Vocabulary

Follows caBIG standards (caDSR/EVS)

XNAT Schema

NIH Mesh and Dublin Core

Deployment Support

Yes, CBIIT Application Support or via NBIA User Listserv

XNAT Google Discussion group, monthly developer tcons, biannual user conference. Commercial technical support provided by Radiologics.

Yes, MIDAS mailing list

Support Operating Systems

Linux, Windows, Mac

Linux, Windows, Mac

Linux, Windows, Mac

Data submission options

Submission to NBIA is performed by a java tool called CTP

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developed by John Perry at the RSNA.  CTP has options to import data from a hard drive or directly from a PACS or DICOM Workstation.

Direct upload is available through the web UI, direct DICOM transfer, scripts using REST API, optimized CTP workflow

Direct upload via web UI, direct DICOM transfer via push, MIDASDesktop transfer (includes command line tools), WebDAV support.

Standard of De-Identification

Incorporates DICOM de-identification standards from The Attribute Confidentiality Profile (DICOM PS 3.15: Appendix E) via CTP.

Built-in de-identification language based on DICOM Browser

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can be configured to comply with DICOM PS 3.15: Appendix E and other standards.

No, but pre-storage filters can be run automatically

Support for multi-site submissions

Yes

Yes

Yes

Include Page
wikicontent:Included Help Downloading Files Panel
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Archive Software

...

NBIA

...

NBIA

...

XNAT

...

Image Data Archive

...

custom

...

XNAT

...

MIDAS

...

MIDAS

...

Active Community

...

Yes

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

Central curation/review

...

Yes

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

Explicit data sharing policy (link)

...

Yes

...

 

...

 

...

 

...

 

...

 

...

Yes

...

 

...

Availability/Uptime

...

99%?

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

Submission Technology

...

CTP

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

Standard of De-Identification

...

Supplement 142 w/ Keep Description, Retain Device Info options enabled

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

Support for multi-site submissions

...

Yes

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

Project- or collection- based groupings?

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

Size of Current Volume

...

~3TB

...

 

...

 

...

 

...

 

...

 

...

None

...

 

...

Federated implementation

...

Yes

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

Public API

...

Yes

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

number of DICOM Tags query-able

...

~90?

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

DICOM transfer protocol

...

For submission, but not download

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

methods to download DICOM data

...

Web, FTP, Java Webstart client

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

Affiliation with Journal

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

Support New Collection?

...

 

...

 

...

 

...

 

...

 

...

 

...

 

...

 

caBIG

NBIA

  • Open source, federated model for grid based image sharing.
  • Allows for "nodes" to be deployed in other institutions, which can then be connected via the grid so they are query-able from any NBIA server.
  • Includes both public data access without login as well as option to build secure role-based Collections which require special access via logging in
  • Simple search query options include node selection, modality, contrast enhancement, anatomical site, image slice thickness, Collections (pre-defined sets of related images), the date the images were made available, and whether or not they have associated annotations
  • Advanced and Dynamic search options available to search upwards of 70 additional DICOM tag attributes
  • Images can be viewed on the web site via JPG thumbnails or using the Cine functionality
  • Allows for storage of annotation files and meta data, though there are plans to move most of this functionality to AIM data services in the near future
  • Downloads are provided in 3 formats, either via a Java webstart client (no size requirement issues, images are not zipped) or HTTP (zipped, for downloads <3GB in size) or an emailed link to an FTP site (zipped, for downloads >3GB in size)
  • Currently 2 major nodes hosted at NCI, one for CIP/CBIIT and another for NIAMS.
    • CIP/CBIIT
      • Contains ~25 purpose built image collections, ~15 of which are publicly accessible to anyone - more info on the contents of each collection can be found at https://wiki.nci.nih.gov/x/lRWy
      • Collections range in size from as small as a handful of patients up to larger collections such as LIDC-IDRI (1010 patients) or the colonoscopy collections (over 800 patients each)
      • Approximately 2.5 TB of image data as of August 2010
    • NIAMS
      • Contains data on nearly 5,000 osteoarthritis patients as of August 2010
      • Modalities include MRI and CR

LONI

LONI homepage: http://www.loni.ucla.edu/

Image Data Archive - http://www.loni.ucla.edu/Research/Databases/

  • Uses LONI Image Data Archive, not sure if this can be deployed and hosted elsewhere for other archives if desired.  Did not immediately notice any place to download the code.
  • Requires secure login, has role based access to various Projects in their archive.
  • Allows search based on project (prior to the simple query page) via Simple or Advanced query.  Simple query contains subject ID, modality, research group, series description, weighting, sex, age, slice thickness, and acquisition plane.  Advanced query offers a wide variety of 27 different search criteria pertaining to the patient, project, clinical info, study info, and image attributes. (Note: advanced query only seems to be an option with ADNI data set)
  • Viewing images in the web site launches "LONI Image Viewer", a java based viewer which lets you scan through image slices in axial/sagittal/coronal orientations as well as zoom, pan, flip (horizontal/vertical) and adjust brightness and contrast.
  • Can add specific series/studies to custom collections, collections can then be downloaded or shared.  Download can be in native DICOM format or in NiFTI/ANALYZE/MINC formats? I've heard of NiFTI, not sure what the other options are.  Download is managed through a java applet, came with images and a couple XML files containing some patient and equipment metadata.
  • Data collections include:
    • Alzheimer's Disease Neuroimaging Initiative (ADNI) - Consists of both image data (MRI and PET), image meta-data, and additional clinical/genetic/numeric summary data for 895 patients
    • BRIN - Logged in with my "ADNI (GUEST)" access this Project only appeared to have one 3 year old patient, no description of this data set is on the "Available Data" page
    • Cryosection Imaging (CRYO) - 3 patients, histology modality
    • Public Anonymized Dataset (PAD) - 3 "normal control" patients, MRI modality
    • International Consortium for Brain Mapping (ICBM) - 851 "normal control" patients, modalities including MRI, fMRI, MRA, DTI, and PET.  I do not have access to this data set currently so did not review its contents.
    • Australian Imaging Biomarkers & Lifestyle Flagship Study of Ageing (AIBL) - 285 patients including controls, MCI, and AD subject groups.  Modalities include MRI and PET.  I do not have access to this data set currently so did not review its contents.

BIRN

BIRN data portal: http://www.birncommunity.org/resources/data/

BIRN is connected with multiple institutions which host multiple archives using different software and containing different data sets.

  • Function BIRN Data Repository - http://fbirnbdr.nbirn.net:8080/BDR/
    • Contains 5 data sets according to the BIRN data page (but it's actually 4). 
    • On the home page it displays a description of each data set and then presents pre-packaged data files in a drill down tree style menu which lists what appears to be individual patients in some cases, individual image studies in others.
    • Querying across the data is possible using meta data.  It does not appear query against DICOM tags is possible.
    • The site itself seems to be a custom web site, not something that could be easily used for other archives.
    • Downloads happen in the browser.  You choose what you want to download, it is processed on the server and there is an alert that notifies you when your "job" is ready for download.  Testing a 100mb patient download I was notified pretty quickly that my job was done, but getting the job page to load took about a minute before I was presented with a small table of information and buttons to actually download the file.  Pressing the download button resulted in saving a .TAR file to my computer.  TAR structure contained many subdirectories sorted by study then series and so on.  Images contained DCM file extension and there were also a couple XML files included with some meta-data.
    • The data sets include the following (but the last one is not yet posted, may never be since this was done in 2007):
      • BrainScape Resting State fMRI Dataset 1 - This dataset includes seventeen healthy subjects with four resting state fixation scans plus one T1 scan and one T2 scan.
      • BrainScape Resting State fMRI Dataset 2 - This dataset includes ten healthy subjects scanned 3 times with 3 conditions: eyes open, eyes closed, and fixating in addition to two anatomical scans (T1 and T2).
      • Neuroimaging Calibration Study (Phase II) - The FBIRN multi-site dataset of subjects with schizophrenia and controls includes functional MRI images, behavioral data, demographic, and clinical assessments on 253 subjects from around the US.
      • Traveling subjects study (Phase I) - This dataset includes five healthy subjects imaged twice at each of ten FBIRN MRI scanners on successive days.
  • NIRL Imaging Database - http://nirlarc.duhs.duke.edu/nirle/
    • Uses XNAT for the archive software (unsure what version or if any major customizations were made)
    • Contains both image data and meta-data
    • Includes the following data sets:
      • Efficient Longitudinal Upload of Depression in the Elderly (ELUDE) - The ELUDE dataset is a longitudinal study of late-life depression at Duke University. There are 281 depressed subjects and 154 controls included (435 total patients). An MR scan of each subject was obtained every 2 years for up to 8 years (total of 1093 scans). Clinical assessments occurred more frequently and consists of a battery of psychiatric tests including several depression-specific tests.
      • Multisite Imaging Research In the Analysis of Depression (MIRIAD) - A multiple institution study of structural MRI, including raw PD and T2 MRIs and derived measures of white matter changes, basal ganglia and other regions. Demographic and extensive clinical assessment data is available for each case. (100 patients)
  • Central XNAT- http://central.xnat.org/

Lung Cancer Alliance: Give A Scan

http://www.giveascan.org/

From their homepage-

*Give A Scan* is the world's first patient-powered, publicly available archive of images and clinical data on lung cancer patients. All the data has been donated by patients in order to encourage more researchers to focus on lung cancer and to accelerate progress in the early detection, diagnosis and treatment of lung cancer which is now the leading cause of cancer death worldwide.

As of August 2010 the archive contains 9 "communities" which appear to be 9 patients with lung cancer totaling approximately 1GB of data.  The site provides some meta data information about the images and clinical info about the subjects.  Images are hosted in DICOM format.  The archive can be browsed by Community/patient/study/series or searched by modality and other image meta data.

The archive is hosted by the Kitware image archive solution called MIDAS: http://www.kitware.com/products/midas.html

Optical Society of America (OSA)

http://midas.osa.org/midaspub/

This archive is a collection of optical images. Like the Lung Cancer Alliance archive it is also hosted using Kitware's MIDAS archive software. This archive hosts 6 top level "communities" which contain anywhere from 4 to 242 items within them. In this case it seems not all of the data is DICOM but some of it is. Three of the Communities appear to be unrelated demonstration collections not tied to OSA as they contain lesion sizing data sets of lung images.

WebMIRS

http://archive.nlm.nih.gov/proj/webmirs/

WebMIRS is the National Library of Medicine's (NLM) tool used for hosting two related datasets and related spine x-ray images which are part of the National Health and Nutrition Examination Survey (NHANES). The site requires registration and login through a java web client to view the data set. Most of the data is text based, but there are spine x-rays for some of the patients. The client allows for searching but not really browsing. The user must enter a boolean search query in order to retrieve any patient results. It does not appear that it is possible to actually download the images, rather that you can only view them in the WebMIRS client.

NA-MIC

National Alliance for Medical Image Computing (NA-MIC) Image Gallery: http://www.na-mic.org/publications/gallery

As of August 2010 this consisted of ~376 images.  All images appear to be JPGs or similar compressed file types rather than actual DICOM.  The purpose of this gallery seems to be to create a repository for images, charts, and figures referenced in publications submitted to NA-MIC's publication database (http://www.na-mic.org/publications).   Images can be browsed by patient/study/series or searched by modality and a number of other image based features.

National Database for Autism Research (NDAR)

http://ndar.nih.gov/ndarpublicweb/aboutNDAR.go

According to http://ndar.nih.gov/ndarpublicweb/aboutNDAR.go#federation-

The Pediatric MRI Data Repository will be the first in this series to be made available to ASD researchers, in the summer of 2010. At that time, investigators will be able to perform a single query in the NDAR portal to view results across multiple datasets.

The original Pediatric MRI Data Repository is located at https://nihpd.crbs.ucsd.edu/nihpd/info/index.html. Access to the data requires filling out multiple forms and faxing them to an office at NIH to receive permission. I have not yet requested access at this time to find out exactly what's in the archive, however some information about their quality control processes reveal a little about the image protocols and can be learned about here: https://nihpd.crbs.ucsd.edu/nihpd/info/quality_control.html

NIH Image Bank

The NIH Image Bank is located at http://media.nih.gov/imagebank/index.aspx

According to http://media.nih.gov/imagebank/about.aspx-

The NIH Image Bank contains images from the collections of the 27 institutes and centers that comprise the National Institutes of Health. Contents include general biomedical and science-related images, clinicians, computers, patient care-related images, microscopy images, and various exterior images.

The point of the image bank appears to be more for promotional and marketing images. I did not notice any high quality medical images of actual patients or DICOM files which might be usable for research purposes.

European Organization for Research and Treatment of Cancer (EORTC)

http://www.eortc.be/services/forms/erp/default.aspx

According to their site investigators can make requests for access to data collected as part of EORTC trials after the primary end point has been published on. I did not see any place that outlined what trials are being conducted, what trials have been completed and reached their publication of primary endpoint, or exactly what types of data are collected. However in the PDF on this page which outlines their data sharing policy in more detail it lists in the section "4.3 Data Transfer" that "data will preferentially transferred in the form of an ASCII file (with .dat extension), with associated SAS programs to load the data into SAS." I saw no mention of how they handle images in this section and thus assume they may not collect or distribute any.

Image archive software solutions

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NBIA

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XNAT

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MIDAS

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OpenPacs

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DCM4CHEE

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Interface/GUI

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Web

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Web

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Query flexibility

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Role Based Security

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Yes

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Public access option

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Yes

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Active Development

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Supports Federated Implementation

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Yes

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API available

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Supported image formats

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Supported metadata formats

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Helpdesk support

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Transfer protocols (import/export)

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Controlled Vocabulary

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Deployment Support

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Support Operating Systems

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Active Development Community

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NBIA

https://gforge.nci.nih.gov/frs/?group_id=312

Xnat

http://www.xnat.org/
http://www.xnat.org/2010+XNAT+Workshop+Agenda

MIDAS

http://www.kitware.com/products/midas.html

OpenPacs

http://www.mii.ucla.edu/index.php/MainSite:OpenSourcePacsDocumentationImageServer

DCM4CHEE

http://www.dcm4che.org/confluence/display/ee2/Home