Motor neuron morphology estimation for its classification in the Drosophila brain

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages7755-7758
Number of pages4
DOIs
StatePublished - Dec 26 2011
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period8/30/119/3/11

Fingerprint

Motor Neurons
Drosophila
Neurons
Brain
Neuronal Plasticity
Carisoprodol
Dendrites
Green Fluorescent Proteins
Confocal Microscopy
Nervous System
Confocal microscopy
Axons
Neurology
Labels
Proteins
Networks (circuits)

ASJC Scopus subject areas

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

Cite this

Tsechpenakis, G., Gamage, R. E., Kim, M. D., & Chiba, A. (2011). Motor neuron morphology estimation for its classification in the Drosophila brain. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 7755-7758). [6091911] https://doi.org/10.1109/IEMBS.2011.6091911

Motor neuron morphology estimation for its classification in the Drosophila brain. / Tsechpenakis, Gavriil; Gamage, Ruwan Egoda; Kim, Michael D.; Chiba, Akira.

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 2011. p. 7755-7758 6091911.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Tsechpenakis, G, Gamage, RE, Kim, MD & Chiba, A 2011, Motor neuron morphology estimation for its classification in the Drosophila brain. in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS., 6091911, pp. 7755-7758, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011, Boston, MA, United States, 8/30/11. https://doi.org/10.1109/IEMBS.2011.6091911
Tsechpenakis G, Gamage RE, Kim MD, Chiba A. Motor neuron morphology estimation for its classification in the Drosophila brain. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 2011. p. 7755-7758. 6091911 https://doi.org/10.1109/IEMBS.2011.6091911
Tsechpenakis, Gavriil ; Gamage, Ruwan Egoda ; Kim, Michael D. ; Chiba, Akira. / Motor neuron morphology estimation for its classification in the Drosophila brain. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 2011. pp. 7755-7758
@inproceedings{6e7eed3de67347f7acd2c41fbd3474d8,
title = "Motor neuron morphology estimation for its classification in the Drosophila brain",
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.",
author = "Gavriil Tsechpenakis and Gamage, {Ruwan Egoda} and Kim, {Michael D.} and Akira Chiba",
year = "2011",
month = "12",
day = "26",
doi = "10.1109/IEMBS.2011.6091911",
language = "English",
isbn = "9781424441211",
pages = "7755--7758",
booktitle = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

}

TY - GEN

T1 - Motor neuron morphology estimation for its classification in the Drosophila brain

AU - Tsechpenakis, Gavriil

AU - Gamage, Ruwan Egoda

AU - Kim, Michael D.

AU - Chiba, Akira

PY - 2011/12/26

Y1 - 2011/12/26

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84055213578&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84055213578&partnerID=8YFLogxK

U2 - 10.1109/IEMBS.2011.6091911

DO - 10.1109/IEMBS.2011.6091911

M3 - Conference contribution

SN - 9781424441211

SP - 7755

EP - 7758

BT - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

ER -