• Corpus ID: 244270290

Interpretability Aware Model Training to Improve Robustness against Out-of-Distribution Magnetic Resonance Images in Alzheimer's Disease Classification

@article{Kuijs2021InterpretabilityAM,
  title={Interpretability Aware Model Training to Improve Robustness against Out-of-Distribution Magnetic Resonance Images in Alzheimer's Disease Classification},
  author={Merel Kuijs and Catherine R. Jutzeler and Bastian Rieck and Sarah Catharina Br{\"u}ningk},
  journal={ArXiv},
  year={2021},
  volume={abs/2111.08701}
}
Owing to its pristine soft-tissue contrast and high resolution, structural magnetic resonance imaging (MRI) is widely applied in neurology, making it a valuable data source for imagebased machine learning (ML) and deep learning applications. The physical nature of MRI acquisition and reconstruction, however, causes variations in image intensity, resolution, and signal-to-noise ratio. Since ML models are sensitive to such variations, performance on out-of-distribution data, which is inherent to… 
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