Published June 9, 2021
| Version v0.1
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Trained model weights for "Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis"
Authors/Creators
- 1. Universtiy Hospital Heidelberg
- 2. Deutsches Krebsforschungszentrum
Description
Trained model weights for "Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis" (https://link.springer.com/article/10.1007/s00330-019-06593-y). Two sets of weights are provided: One for prediction with T1 and one for prediction without T1 modality.
Files
ms_lesions_weights.zip
Files
(2.3 GB)
| Name | Size | Download all |
|---|---|---|
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md5:3e7697399a8c9723b48e67a7013deebc
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2.3 GB | Preview Download |
Additional details
References
- Brugnara, Gianluca et al. (2020). Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis