Dendritic spine classification using shape and appearance features based on two-photon microscopy.

Journal: Journal of neuroscience methods
PMID: 27998713

Abstract

BACKGROUND: Neuronal morphology and function are highly coupled. In particular, dendritic spine morphology is strongly governed by the incoming neuronal activity. The first step towards understanding the structure-function relationships is to classify spine shapes into the main spine types suggested in the literature. Due to the lack of reliable automated analysis tools, classification is mostly performed manually, which is a time-intensive task and prone to subjectivity.

Authors

  • Muhammad Usman Ghani
    Signal Processing and Information Systems Lab., Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey. Electronic address: mughani@bu.edu.
  • Fitsum Mesadi
    Electrical and Computer Engineering Department, University of Utah, Salt Lake City, UT, USA.
  • Sümeyra Demir Kanık
    Signal Processing and Information Systems Lab., Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey.
  • Ali Özgür Argunşah
    Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal. Electronic address: argunsah@hifo.uzh.ch.
  • Anna Felicity Hobbiss
    Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal.
  • Inbal Israely
    Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal. Electronic address: ii2176@cumc.columbia.edu.
  • Devrim Ünay
    Biomedical Engineering Department, Faculty of Engineering, Izmir University of Economics, Izmir, Turkey.
  • Tolga Tasdizen
    Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.
  • Müjdat Çetin

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