3D MRI brain tumor segmentation using autoencoder regularization

doi:doi:10.57702/onlae694

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3D MRI brain tumor segmentation using autoencoder regularization

Automated segmentation of 3D brain tumors from 3D magnetic resonance images (MRIs) is necessary for the diagnosis, monitoring, and treatment planning of the disease.

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The json representation of the dataset with its distributions based on DCAT.
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Andriy Myronenko (2025). Dataset: 3D MRI brain tumor segmentation using autoencoder regularization. https://doi.org/10.57702/onlae694

DOI retrieved: January 2, 2025

Additional Info

Field	Value
Created	January 2, 2025
Last update	January 2, 2025
Defined In	https://doi.org/10.48550/arXiv.1810.11654
Author	Andriy Myronenko
Homepage	https://www.cbica.upenn.edu/BraTS18/lboardValidation.html