Data Access
Data Type | Download all or Query/Filter | License |
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Images (DICOM, 4.4 GB) |
Prostate Fused-MRI-Pathology |
(Download requires the NBIA Data Retriever) | | Annotated Whole Slide Pathology Images & Annotations (Tiff, XML 76.8 GB) |
(Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) | | Fused Rad-Path Matlab Files (zip, 65 kB) | | | Correspondence tables (XLSX, 22 kB) | | |
Click the Versions tab for more info about data releases. |
Detailed Description
| | Pathology Image Statistics |
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Modalities | MRI | Pathology, Matlab | Number of Participants | 28 | 16 | Number of Studies | 28 | N/A | Number of Series | 324 | N/A | Number of Images | 32,508 | 114 | Image Size (GB) | 4.4 | 76.8 |
Supporting DocumentationThe data set is fully described in the following publications: Singanamalli, A. , Rusu, M. , Sparks, R. E., Shih, N. N., Ziober, A. , Wang, L. , Tomaszewski, J. , Rosen, M. , Feldman, M. and Madabhushi, A. (2016), Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer. J. Magn. Reson. Imaging, 43: 149-158. doi: https://doi.org/10.1002/jmri.24975 (PMID:26110513). - Toth, R, Feldman, M, Yu, D, Tomaszewski, J, Madabhushi, A, “Histostitcher™: An Informatics Software Platform for Reconstructing Whole-Mount Prostate Histology using the Extensible Imaging Platform (XIP™) Framework,” Journal of Pathology Informatics, vol. 5, pg. 8, 2014 (PMID: 24843820, PMCID: PMC4023035). https://doi.org/10.4103/2153-3539.129441
- Xiao, G, Bloch, N, Chappelow, J, Genega, E, Rofsky, N, Lenkinsky, R, Tomaszewski, J, Feldman, M, Rosen, M, Madabhushi, A, “Determining Histology-MRI Slice Correspondences for Defining MRI-based Disease Signatures of Prostate Cancer,” Special Issue of Computerized Medical Imaging and Graphics on Whole Slide Microscopic Image Processing, vol. 35[7-8], pp. 568-78, 2011 (PMID: 21255974). https://doi.org/10.1016/j.compmedimag.2010.12.003
- Chappelow, J, Bloch, N., Rofsky, N, Genega, E, Lenkinski, R, DeWolf, W, Madabhushi, A, “Elastic Registration of Multimodal Prostate MRI and Histology via Multi-Attribute Combined Mutual Information,” Medical Physics, vol. 38[4], pp. 2005-2018, 2011 (PMID: 21626933). https://doi.org/10.1118/1.3560879
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Citations & Data Usage Policy Madabhushi, A., & Feldman, M. (2016). Fused Radiology-Pathology Prostate Dataset (Prostate Fused-MRI-Pathology) . The Cancer Imaging Archive. doi; 10.7937/k9/TCIA.2016.tlpmr1am |
Singanamalli, A. , Rusu, M. , Sparks, R. E., Shih, N. N., Ziober, A. , Wang, L. , Tomaszewski, J. , Rosen, M. , Feldman, M. and Madabhushi, A. (2016), Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer. J. Magn. Reson. Imaging, 43: 149-158. doi: 10.1002/jmri.24975 (PMID:26110513). |
Toth, R, Feldman, M, Yu, D, Tomaszewski, J, Madabhushi, A, “Histostitcher™: An Informatics Software Platform for Reconstructing Whole-Mount Prostate Histology using the Extensible Imaging Platform (XIP™) Framework,” Journal of Pathology Informatics, vol. 5, pg. 8, 2014 (PMID: 24843820, PMCID: PMC4023035). https://doi.org/10.4103/2153-3539.129441 |
Xiao, G, Bloch, N, Chappelow, J, Genega, E, Rofsky, N, Lenkinsky, R, Tomaszewski, J, Feldman, M, Rosen, M, Madabhushi, A, “Determining Histology-MRI Slice Correspondences for Defining MRI-based Disease Signatures of Prostate Cancer,” Special Issue of Computerized Medical Imaging and Graphics on Whole Slide Microscopic Image Processing, vol. 35[7-8], pp. 568-78, 2011 (PMID: 21255974). https://doi.org/10.1016/j.compmedimag.2010.12.003 |
Chappelow, J, Bloch, N., Rofsky, N, Genega, E, Lenkinski, R, DeWolf, W, Madabhushi, A, “Elastic Registration of Multimodal Prostate MRI and Histology via Multi-Attribute Combined Mutual Information,” Medical Physics, vol. 38[4], pp. 2005-2018, 2011 (PMID: 21626933). https://doi.org/10.1118/1.3560879 |
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: https://doi.org/10.1007/s10278-013-9622-7 |
Other Publications Using This DataTCIA maintains a list of publications which leverage our data. If you have a publication you'd like to add, please contact TCIA's Helpdesk. - Brunese, L., Mercaldo, F., Reginelli, A., & Santone, A. (2020). Formal methods for prostate cancer gleason score and treatment prediction using radiomic biomarkers. Magnetic resonance imaging, 66, 165-175. doi:https://doi.org/10.1016/j.mri.2019.08.030
- Chatzoudis, P. (2018). MRI prostate cancer radiomics: Assessment of effectiveness and perspectives. (Master of Biomedical Engineering). Delft University of Technology, Delft, Netherlands. Retrieved from http://resolver.tudelft.nl/uuid:b8459bdb-1761-4f17-8807-e3b1cf7da629
- Duran, A., Dussert, G., Rouviere, O., Jaouen, T., Jodoin, P. M., & Lartizien, C. (2022). ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans. Medical image analysis, 77, 102347. doi:https://doi.org/10.1016/j.media.2021.102347
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Version 2 (Current): Updated 2023/04/10Data Type | Download all or Query/Filter | License |
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Images (DICOM, 4.4 GB) |
Prostate Fused-MRI-Pathology |
(Download requires the NBIA Data Retriever) | | Annotated Whole Slide Pathology Images & Annotations (Tiff, XML 76.8 GB) | (Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) | | Fused Rad-Path Matlab Files | | | Correspondence tables (XLSX) | | |
Added a correspondence xlsx between MR and Pathology slides, imaging data are unchanged. Version 1: Updated 2016/11/30
Data Type | Download all or Query/Filter |
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Images (DICOM, 4.4 GB) |
(Download requires the NBIA Data Retriever) | Annotated Whole Slide Pathology Images & Annotations (Tiff, XML 76.8 GB) |
(Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) | Fused Rad-Path MATLAB Files | |
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