Motor neuron morphology estimation for its classification in the Drosophila brain.

Gavriil Tsechpenakis, Ruwan Egoda Gamage, Michael D. Kim, Akira Chiba

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Type-specific dendritic arborization patterns dictate synaptic connectivity and are fundamental determinants of neuronal function. We exploit the morphological stereotypy and relative simplicity of the Drosophila nervous system to model the diverse dendritic morphologies of individual motor neurons (MNs) to understand underlying principles of synaptic connectivity in a motor circuit. The genetic tractability of Drosophila allows us to label single MNs with green fluorescent protein (GFP) and serially reconstruct identifiable MNs in 3D with confocal microscopy. Our computational approach aims at the robust segmentation of the MN volumes and the simultaneous partitioning into their compartments, namely the soma, axon and dendrites. We use the idea of co-segmentation, where every image along the z-axis (depth) is clustered using information from 'neighboring' depths. As appearance we use a 3D extension of Haar features and for the shape we define an implicit representation of the segmentation domain.

Original languageEnglish
Pages (from-to)7755-7758
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Volume2011
StatePublished - Dec 1 2011
Externally publishedYes

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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