Child pages
  • High Resolution Prostate Segmentations for the ProstateX-Challenge (PROSTATEx-Seg-HiRes)

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

Compare with Current View Page History

« Previous Version 79 Next »


Example of a high resolution segmentation. The segmentation is smooth in all directions and does not suffer from step artifacts

We created 66 high resolution segmentations for randomly chosen T2-weighted volumes of the SPIE-AAPM-NCI PROSTATEx Challenges. The high resolution segmentations were obtained by considering the three scan directions: for each scan direction (axial, sagittal, coronal), the gland was manually delineated by a medical student, followed by a review and corrections of an expert urologist. These three anisotropic segmentations were fused to one isotropic segmentation by means of shape-based interpolation in the following manner: (1) The signed distance transformation of the three segmentations is computed. (2) The anisotropic distance volumes are transformed into an isotropic high-resolution representation with linear interpolation. (3) By averaging the distances, smoothing and thresholding them at zero, we obtained the fused segmentation. The resulting segmentations were manually verified and corrected further by the expert urologist if necessary. Serving as ground truth for training CNNs, these segmentations have the potential to improve the segmentation accuracy of automated algorithms. By considering not only the axial scans but also sagittal and coronal scan directions, we aimed to have higher fidelity of the segmentations especially at the apex and base regions of the prostate.

The segmentations to standard DICOM representation were created with dcmqi .


  • This work has been funded by the EU and the federal state of Saxony-Anhalt, Germany under grant number ZS/2016/08/80388.

Data Access

Click the Download  button to save a ".tcia" manifest file to your computer, which you must open with the  NBIA Data Retriever.

Data TypeDownload all or Query/Filter
Segmentations (DICOM, 0.119 GB)


Corresponding Original MR Images from PROSTATEx (DICOM, 371.21 MB)


Collections Used in this Third Party Analysis
Below is a list of the Collections used in these analyses:

Detailed Description

Image Statistics
Number of Patients66
Number of Studies66
Number of Series66

Number of Images

Image Size (GB)0.119

Note:   Please contact  with any questions regarding usage.

Citations & Data Usage Policy 

Users of this data must abide by the TCIA Data Usage Policy and the Creative Commons Attribution 3.0 Unported License under which it has been published. Attribution should include references to the following citations:

Dataset Citation

Schindele, D., Meyer, A., Von Reibnitz, D. F., Kiesswetter, V., Schostak, M., Rak, M., & Hansen, C. (2020). High Resolution Prostate Segmentations for the ProstateX-Challenge [Data set]. The Cancer Imaging Archive.

Publication Citation

Meyer, A., Chlebus, G., Rak, M., Schindele, D., Schostak, M., van Ginneken, B., Schenk, A., Meine, H., Hahn, H. K., Schreiber, A., & Hansen, C. (2020). Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI. Computer Methods and Programs in Biomedicine, 105821.

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 that leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.

Version 1 (Current): 2020/09/18

Data TypeDownload all or Query/Filter
Segmentations (DICOM, 0.119 GB)


Corresponding Original MR Images from PROSTATEx (DICOM, 371.21 MB)



  • No labels