Neurocounter - A deep learning framework for high-fidelity spatial localization of neurons.

Journal: Journal of neuroscience methods
Published Date: Apr 3, 2025

Abstract

BACKGROUND: Many neuroscientific applications require robust and accurate localization of neurons. It is still an unsolved problem because of the enormous variation in intensity, texture, spatial overlap, morphology, and background artifacts. In addition, curating a large dataset containing complete manual annotation of neurons from high-resolution images for training a classifier requires significant time and effort. In this work, we presented Neurocounter, a deep learning network to detect and localize neurons.

Authors

  • Tamal Batabyal
    Department of Neurology, University of Virginia, Charlottesville, VA 22908, USA. Electronic address: tb2ea@virginia.edu.
  • Aijaz Ahmad Naik
    Department of Neurology, University of Virginia, Charlottesville, VA 22908, USA.
  • Jaideep Kapur
    Department of Neurology, University of Virginia, Charlottesville, VA 22908, USA; UVA Brain Institute, University of Virginia, Charlottesville, VA 22908, USA.

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