Dataset Open Access

Augmentation Via Registration: AutoImplant 2020 Augmented Data Set

David G Ellis

Augmented data derived from the AutoImplant 2020 Challenge. Data has been augmented via non-linear SyN registrations using Advanced Normalization Tools (ANTs). This data was used to obtain first place in the AutoImplant 2020 challenge. The AutoImplant 2020 Challenge data was derived from the QC500 dataset from qure.ai. The original dataset is licensed under the CC BY-NC-SA 4.0 license (Attribution-NonCommercial-ShareAlike) and complies with the End User License Agreement (EULA) which are both detailed in the "LICENSE" file in this folder. Please refer to the "LICENSE" file for terms of use.

If you use this data, please cite the following paper:

Ellis D.G., Aizenberg M.R. (2020) Deep Learning Using Augmentation via Registration: 1st Place Solution to the AutoImplant 2020 Challenge. In: Li J., Egger J. (eds) Towards the Automatization of Cranial Implant Design in Cranioplasty. AutoImplant 2020. Lecture Notes in Computer Science, vol 12439. Springer, Cham. https://doi.org/10.1007/978-3-030-64327-0_6

Files (10.6 GB)
Name Size
augmented_autoimplant2020_data.tar.gz
md5:8374aebc4ff866d15dab1e3f2d49ef0f
10.6 GB Download
LICENSE
md5:1dfa11e24964df6e120ec2522ffd6272
11.9 kB Download
README
md5:2188c8b16b054faea66e7934cba5630a
1.0 kB Download
  • Ellis D.G., Aizenberg M.R. (2020) Deep Learning Using Augmentation via Registration: 1st Place Solution to the AutoImplant 2020 Challenge. In: Li J., Egger J. (eds) Towards the Automatization of Cranial Implant Design in Cranioplasty. AutoImplant 2020. Lecture Notes in Computer Science, vol 12439. Springer, Cham. https://doi.org/10.1007/978-3-030-64327-0_6

309
5,817
views
downloads
All versions This version
Views 309309
Downloads 5,8175,817
Data volume 61.2 TB61.2 TB
Unique views 271271
Unique downloads 613613

Share

Cite as