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This collection comprises 25 patients with Manufacturer CT at Veteran's Hospital before treatment and 2 follow up T1-weighted and FLAIR MRI along with accompanying digitized histopathology (H&E stained) images of corresponding biopsy specimens. Each slide was digitized at 10x magnification using an Aperio slide scanner resulting in a set of .svs images. Annotations of cancer presence on the pseudo-whole mount sections were made by an expert pathologist. Segmentation was performed with by Software (github, below) and compared to expert radiologist segmentation. co-registered the corresponding radiologic and histopathologic tissue sections to map disease extent onto the corresponding MRI scans. Co-clinical data that led to this therapy in humans is available within TCIA (here) as ThisOther Collection. For more information about the original aims of this trial please see:


DICOM Data was provided by Principal Investigator, PhD, University of City and Co-Investigator, MD, City Veteran's Hospital. This work was supported by NIH Grant (link). Pathology segmentations were performed by Helpful Expert, MD. 


  1. Prior F, Clark K, Commean P, Freymann J, Jaffe C, Kirby J, et al. TCIA: an information resource to enable open science.  Engineering in Medicine and Biology Society (EMBC), 35th Int’l Conf of the IEEE, Osaka: IEEE; 2013:1282-5.  PMCID: PMC4257783 DOI: 10.1109/EMBC.2013.6609742

  2. Moore S, Maffitt D, Smith K, Kirby J, Clark K, Freymann J, et al. De-identification of Medical Images with Retention of Scientific Research Value. RadioGraphics. 2015;35:3:727-35. DOI: 10.1148/rg.2015140244

 For scientific inquiries about this dataset, please contact Junior Investigator through the TCIA Helpdesk: 

Data Access (Radiology)

 Choosing the Download option will provide you with a file to launch the TCIA Download Manager to download the entire collection. If you want to browse or filter the data to select only specific scans/studies please use the Search option.

Data TypeDownload all or Query/Filter
Images (DICOM, GB) 

DICOM Metadata Digest (CSV)

Annotated Whole Slide Pathology Images
Fused Rad-Path Matlab Files

Clinical Data (xls, MB)

Detailed genomic and expression array data (External Link)

Radiologist Annotations/Segmentations (XML)
Nodule Size List (web)

Pathology and Matlab Data

Reconstructed, annotated whole slide pathology as well as fused Rad-Path matlab objects are also available at

Segmentation Software

Myscriptsandthings was written to convert the XML into a visualization in python.  It is available for download as a community tool here as a container and at in developer versions.

Click the Versions tab for more info about data releases.

Detailed Description

Collection Statistics




Number of Patients


Number of Studies

Number of Series

Number of Images

Image Size (GB)

Supporting Documentation

The data set is fully described in the following publications: 


Citations & Data Usage Policy 

 This collection is freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License.  See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to

Please be sure to include the following citations in your work if you use this data set:

Data Citation

Madabhushi, A., & Feldman, M. (2016). Fused Radiology-Pathology Prostate Dataset. The Cancer Imaging Archive.

Publication Citation


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. (paper)

Other Publications Using This Data

TCIA maintains a list of publications which leverage our data. At this time we are not aware of any publications based on this data. If you have a publication you'd like to add please contact the TCIA Helpdesk.


Version 1 (Current) Updated 11-30-2016

Data TypeDownload all or Query/Filter
Images (DICOM, 4.4 GB) 
Annotated Whole Slide Pathology Images
Fused Rad-Path MATLAB Files



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