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Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 5)

<p>Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 5)</p> <p>https://sites.google.com/view/icassp2024-spgc-3dcbct/home</p> <p>Please download all files (of all parts, 1-5) into one folder, and then merge them together with:</p> <p>$ zip -s 0 train.zip --out train_unsplit.zip</p> <p>&nbsp;</p> <p>This will create a new zip file, &quot;train_unsplit.zip&quot; that then you can unzip with your favorite tool, e.g.</p> <p>$ unzip train_unsplit.zip</p> <p>&nbsp;</p> <p><br> The CBCT geometry required to be used</p> <p>image size : [300 300 300] mm<br> image shape : [256 256 256] voxels<br> voxel size : [1.171875 1.171875 1.171875] mm<br> detector shape : [256 256] pixels<br> detector size : [600, 600]&nbsp; mm<br> pixel size : [2.34375, 2.34375] mm<br> distance source origin (axis of rotation, center of image) : 575 mm<br> distance source to detector : 1050 mm</p> <p>&nbsp;</p> <p>We recommend zenodo_get to download the files:<br> <a href="https://github.com/dvolgyes/zenodo_get">https://github.com/dvolgyes/zenodo_get</a></p> <p><br> Remember that to be part of the challenge you need to register in the webpage above.</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0