• Corpus ID: 239016728

DBSegment: Fast and robust segmentation of deep brain structures - Evaluation of transportability across acquisition domains

@article{Baniasadi2021DBSegmentFA,
  title={DBSegment: Fast and robust segmentation of deep brain structures - Evaluation of transportability across acquisition domains},
  author={Mehri Baniasadi and Mikkel V Petersen and Jorge Gonçalves and Andreas Horn and Vanja Vlasov and Frank Hertel and Andreas Dominik Husch},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.09473}
}
Segmenting deep brain structures from magnetic resonance images is important for patient diagnosis, surgical planning, and research. Most current state-of-the-art solutions follow a segmentation-byregistration approach, where subject MRIs are mapped to a template with well-defined segmentations. However, registration-based pipelines are time-consuming, thus, limiting their clinical use. This paper uses deep learning to provide a robust and efficient deep brain segmentation solution. The method… 

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