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Abstract: FastSurfer

A Fast and Accurate Deep Learning Based Neuroimaging Pipeline
  • Leonie Henschel
  • Sailesh Conjeti
  • Santiago Estrada
  • Kersten Diers
  • Bruce Fischl
  • Martin ReuterEmail author
Conference paper
  • 57 Downloads
Part of the Informatik aktuell book series (INFORMAT)

Zusammenfassung

Traditional neuroimage analysis pipelines involve computationally intensive, time-consuming optimization steps, and thus, do not scale well to large cohort studies. With FastSurfer [1] we propose a fast deep-learning based alternative for the automated processing of structural human MRI brain scans, including surface reconstruction and cortical parcellation. FastSurfer consists of an advanced deep learning architecture (FastSurferCNN) used to segment a whole brain MRI into 95 classes in under 1 min, and a surface pipeline building upon this high-quality brain segmentation.

Literatur

  1. 1.
    Henschel L, Conjeti S, Estrada S, et al. FastSurfer – a fast and accurate deep learning based neuroimaging pipeline. CoRR. 2019;abs/1910.03866.Google Scholar

Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2020

Authors and Affiliations

  • Leonie Henschel
    • 1
  • Sailesh Conjeti
    • 1
  • Santiago Estrada
    • 1
  • Kersten Diers
    • 1
  • Bruce Fischl
    • 2
    • 3
    • 4
  • Martin Reuter
    • 1
    • 2
    • 3
    Email author
  1. 1.German Center for Neurodegenerative Diseases (DZNE)BonnDeutschland
  2. 2.A.A. Martinos Center for Biomedical ImagingMGHBostonUSA
  3. 3.Department of RadiologyHarvard Medical SchoolBostonUSA
  4. 4.Computer Science and Artificial Intelligence LaboratoryMITCambridgeUSA

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