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Renato Cuocolo
2021-02-20 18:07:19 +01:00
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@@ -50,6 +50,17 @@ The sequence number corresponds to the number at the beginning of the PROSTATEx
Full exam DICOM files are retrievable through the Cancer Imaging Archive at: [https://wiki.cancerimagingarchive.net/display/Public/SPIE-AAPM-NCI+PROSTATEx+Challenges](https://wiki.cancerimagingarchive.net/display/Public/SPIE-AAPM-NCI+PROSTATEx+Challenges)
## Citation
The article is still in production, but has been assigned a DOI. Details are:
Journal: Journal of Magnetic Resonance Imaging
Article DOI: 10.1002/jmri.27585
Article: Deep learning whole-gland and zonal prostate segmentation on a public MRI dataset
Authors: Renato Cuocolo, Albert Comelli, Alessandro Stefano, Viviana Benfante, Navdeep Dahiya, Arnaldo Stanzione, Anna Castaldo, Davide Raffaele De Lucia, Anthony Yezzi, Massimo Imbriaco
Formatted for typical journal use: Cuocolo R, Comelli A, Stefano A, et al (2021) Deep learning whole-gland and zonal prostate segmentation on a public MRI dataset. J Magn Reson Imaging. https://doi.org/10.1002/jmri.27585
## License
Creative Commons Attribution 4.0 International (CC-BY-4.0). See "LICENSE" file for full details.