Summary
This collection contains prostate’s zonal segmentation for 98 cases randomly selected from the SPIE-AAPM-NCI PROSTATEx Challenge. The four-class segmentation encompasses the peripheral zone, transition zone, fibromuscular stroma and the distal prostatic urethra. As underlying images, we used transversal T2w scans. Segmentations were created by a medical student with experience in prostate segmentation and an expert urologist who instructed the student and double-checked the segmentations in the end. The DICOM representation of these segmentations were generated with dcmqi.
Note: If this dataset is used for commercial purposes, please contact office@isg.cs.uni-magdeburg.de
Acknowledgements
- This work has been funded by the EU and the federal state of Saxony-Anhalt, Germany under grant number ZS/2016/08/80388. We would like to thank the authors of the PROSTATEx challenge for providing this valuable dataset
Data Access
Data Type | Download all or Query/Filter |
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Segmentations (DICOM, GB) | |
Corresponding Original MR Images from PROSTATEx (DICOM, MB) |
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Detailed Description
Image Statistics | |
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Modalities | SEG |
Number of Patients | 98 |
Number of Studies | 98 |
Number of Series | 98 |
Number of Images | 98 |
Images Size (GB) |
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Citations & Data Usage Policy
Data Citation
Schindele, D., Meyer, A., Von Reibnitz, D. F., Schostak, M., Rak, M., & Hansen, C. (2020). PROSTATEx Zone Segmentations. The Cancer Imaging Archive. https://doi.org/10.7937/tcia.nbb4-4655
Publication Citation
Meyer, M. Rak, D. Schindele, S. Blaschke, M. Schostak, A. Fedorov, C. Hansen, “Towards Patient-Individual PI-RADS v2 Sector Map: CNN for Automatic Segmentation of Prostatic Zones from T2-Weighted MRI”, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), Venice, Italy, 2019, pp. 696-700, doi: 10.1109/ISBI.2019.8759572.
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
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