A Practical Roadmap to Implementing Deep Learning Segmentation in the Clinical Neuroimaging Research Workflow.

Journal: World neurosurgery
Published Date: Jun 10, 2024

Abstract

BACKGROUND: Thanks to the proliferation of open-source tools, we are seeing an exponential growth of machine-learning applications, and its integration has become more accessible, particularly for segmentation tools in neuroimaging.

Authors

  • Marco Pérez Cáceres
    Department of Radiology, University of Montreal, Montréal, Québec, Canada. Electronic address: marco.perez.caceres@umontreal.ca.
  • Alexandre Gauvin
    Department of Neurosurgery, CHUS (Centre Hôspitalier de L'Université de Sherbrooke) Fleurimont Hospital, Montréal, Québec, Canada.
  • Félix Dumais
    Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health Science, Université de Sherbrooke, 3001 12e Avenue N, Sherbrooke, Québec J1H 5H3, Canada. Electronic address: felix.dumais@usherbrooke.ca.
  • Christian Iorio-Morin
    Department of Neurosurgery, CHUS (Centre Hôspitalier de L'Université de Sherbrooke) Fleurimont Hospital, Montréal, Québec, Canada.

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