Child pages
  • Segmentation and Classification of Grade I and II Meningiomas from Magnetic Resonance Imaging: An Open Annotated Dataset (Meningioma-SEG-CLASS)

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 2 Next »

Summary

The study included 96 consecutive treatment naïve patients with intracranial meningiomas treated with surgical resection from 2010 to 2019. All patients had pre-operative T1, T1-CE, and T2-FLAIR MR images with subsequent subtotal or gross total resection of pathologically confirmed Grade I or grade II meningiomas. A neuropathology team reviewed histopathology, including two subspecialty trained neuropathologists and one neuropathology fellow. The meningioma grade was confirmed based on current classification guidelines, most recently described in the 2016 WHO Bluebook. Clinical information includes grade, subtype, type of surgery, tumor location, and atypical features. Meningioma labels on T1ce and T2-FLAIR images will also be provided in DICOM format.

Other researchers can use the data to build deep learning models to predict meningioma grade I and II based on diagnostic MR images (T1CE and T2-FLAIR).

Acknowledgements

We would like to acknowledge the individuals and institutions that have provided data for this collection:



Data Access

Some data in this collection contains images that could potentially be used to reconstruct a human face. To safeguard the privacy of participants, users must sign and submit a TCIA Restricted License Agreement to help@cancerimagingarchive.net before accessing the data.

Data TypeDownload all or Query/FilterLicense

Images, Segmentations, and Radiation Therapy Structures/Doses/Plans (DICOM, XX.X GB)

<< latter two items only if DICOM SEG/RTSTRUCT/RTDOSE/PLAN exist >>

   

(Download requires NBIA Data Retriever)

Tissue Slide Images (SVS, XX.X GB)

   

(Download requires Aspera plugin)
Clinical data (CSV)

Click the Versions tab for more info about data releases.


Detailed Description

Image Statistics

Radiology Image StatisticsPathology Image Statistics

Modalities

MR


Number of Patients

96


Number of Studies



Number of Series



Number of Images



Images Size (GB)

Citations & Data Usage Policy

Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:

Data Citation

DOI goes here. Create using Datacite with information from Collection Approval form

Publication Citation

We ask on the proposal form if they have ONE traditional publication they'd like users to cite.

TCIA Citation

Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7

Other Publications Using This Data

TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.

Version X (Current): Updated yyyy/mm/dd

Data TypeDownload all or Query/FilterLicense

Images, Segmentations, and Radiation Therapy Structures/Doses/Plans (DICOM, XX.X GB)

<< latter two items only if DICOM SEG/RTSTRUCT/RTDOSE/PLAN exist >>

    (Download requires the NBIA Data Retriever)

Tissue Slide Images (SVS, XX.X GB)
Clinical data (CSV)



  • No labels