Hidden Markov modeling for maximum probability neuron reconstruction

Thomas L. Athey; Daniel J. Tward; Ulrich Mueller; Joshua T. Vogelstein; Michael I. Miller

doi:10.1038/s42003-022-03320-0

Communications Biology (Apr 2022)

Hidden Markov modeling for maximum probability neuron reconstruction

Thomas L. Athey,
Daniel J. Tward,
Ulrich Mueller,
Joshua T. Vogelstein,
Michael I. Miller

Affiliations

Thomas L. Athey: Department of Biomedical Engineering, Johns Hopkins University
Daniel J. Tward: Department of Computational Medicine, University of California at Los Angeles
Ulrich Mueller: Department of Neuroscience, Johns Hopkins University
Joshua T. Vogelstein: Department of Biomedical Engineering, Johns Hopkins University
Michael I. Miller: Department of Biomedical Engineering, Johns Hopkins University

DOI: https://doi.org/10.1038/s42003-022-03320-0
Journal volume & issue: Vol. 5, no. 1
pp. 1 – 11

Abstract

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ViterBrain is an automated probabilistic reconstruction method that can reconstruct neuronal geometry and processes from microscopy images with code available in the open-source Python package, brainlit.

Published in Communications Biology

ISSN: 2399-3642 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science: Biology (General)
Website: https://www.nature.com/commsbio/

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