Summary
Abstract: We created 66 high resolution segmentations for randomly chosen T2-weighted volumes of the ProstateX challenge. 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.
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title | Data Access |
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| Data AccessClick the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever. Data Type | Download all or Query/Filter |
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Segmentation Images (DICOM #.# GB) | | Corresponding Original MR Images from PROSTATEx (DICOM, 1.0 GB) | | UID Patient ID List (TXT) | |
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title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy These collections are freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. Questions may be directed to help@cancerimagingarchive.net. Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work: Info |
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| Schindele, D., Meyer, A., Von Reibnitz, D. F., Kiesswetter, V., Schostak, M., Rak, M., & Hansen, C. (2019). High Resolution Prostate Segmentations for the ProstateX-Challenge [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.2019.DEG7ZG1U |
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| 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 |
In addition to the dataset citation above, please be sure to cite the following if you utilize these data in your research: Info |
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title | Publication Citation |
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| Version 1 (Current): 2020/01/08Data Type | Download all or Query/Filter |
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Segmentation Images (DICOM #.# GB) | | Corresponding Original MR Images from PROSTATEx (DICOM, 1.0 GB) | | UID Patient ID List (TXT) | |
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