Test Dataset for 3D semantic image segmentation of the various organs from CT and MR scans
<p>These test cases are for the <a href="https://github.com/MIC-DKFZ/nnUNet/releases/tag/v1.7.1">nnUnet v1</a> models trained on the following datasets:<br><br></p> <table> <tbody> <tr> <td>Dataset </td> <td>Task</td> <td>Model Details on Zenodo</td> </tr> <tr> <td> <a href="../record/6802614">TotalSegmentator</a> and <a href="../record/5903672">FLARE21</a> datasets</td> <td>Segment Liver from CT scans</td> <td>https://zenodo.org/record/8274976</td> </tr> <tr> <td><a href="https://kits-challenge.org/kits23/">KiTS23</a> datasets and a subset of the<a href="https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=5800386#5800386566e265abf95408aa64c4917f0cbe5d9"> TCGA-KIRC </a>dataset</td> <td>Segment Kidney, Cyst, and Tumors from CT Scans</td> <td>https://zenodo.org/records/8277846</td> </tr> <tr> <td><a href="http://ji%20yuanfeng.%20(2022).%20amos%20a%20large-scale%20abdominal%20multi-organ%20benchmark%20for%20versatile%20medical%20image%20segmentation%20[data%20set].%20zenodo.%20https">AMOS</a> and <a href="http://macdonald,%20jacob%20a.,%20zhu,%20zhe,%20konkel,%20brandon,%20mazurowski,%20maciej,%20wiggins,%20walter,%20&%20bashir,%20mustafa.%20(2020).%20duke%20liver%20dataset%20(mri)%20v2%20(2.0.0)%20[data%20set].%20zenodo.%20https//doi.org/10.5281/zenodo.7774566">DUKE Liver</a> datasets</td> <td>Segment Liver from the MR scans</td> <td>https://zenodo.org/record/8290124</td> </tr> <tr> <td>Data from m <a href="../record/6624726">pi-cai</a></td> <td>Segment Prostate region from MR scans</td> <td>https://zenodo.org/record/8290093</td> </tr> </tbody> </table>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 8
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0