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PROSTATEX-SEG-HIRES

PROSTATEx-Seg-HiRes | High Resolution Prostate Segmentations for the ProstateX-Challenge

DOI: 10.7937/TCIA.2019.DEG7ZG1U | Data Citation Required | Analysis Result

Cancer Types Location Subjects Related Collections Size Supporting Data Updated
Prostate Prostate 66 125.17MB Organ segmentations 2020/09/18

Summary

We created 66 high resolution segmentations for randomly chosen T2-weighted volumes of the SPIE-AAPM-NCI PROSTATEx Challenges (PROSTATEx). 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 

Data Access

Version 1: Updated 2020/09/18

Title Data Type Format Access Points Subjects Studies Series Images License
Segmentations SEG DICOM
Download requires NBIA Data Retriever
66 66 66 66 CC BY 3.0

Collections Used In This Analysis Result

Title Data Type Format Access Points Subjects Studies Series Images License
Corresponding Original MR Images from PROSTATEx MR DICOM 66 66 66 1,361 CC BY 3.0

Citations & Data Usage Policy

Data Citation Required: Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution must include the following citation, including the Digital Object Identifier:

Data 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. https://doi.org/10.7937/TCIA.2019.DEG7ZG1U

Acknowledgements

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

Publications Using This Data

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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. https://doi.org/10.1016/j.cmpb.2020.105821

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. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7

Collections Used In This Analysis Result

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