Part-wise neuron segmentation using artificial templates

S. Gulyanon, N. Sharifai, M. D. Kim, A. Chiba, G. Tsechpenakis

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


Our goal is to analyze neuronal morphology during development using artificially created templates. Such templates serve as input from the domain expertise: a standardized representation of the neuron, independent from imaging modalities and resolution, is what a neurobiologist can provide from knowledge and qualitative observations in the microscope. A template is divided into context-specific (topology, shape, and/or function) compartments, and our task is to segment input neuron volumes from their surroundings and partition them accordingly. We solve this problem using a global-to-local approach. We first employ a global transformation that serves as part-wise alignment of the template with the input volume. Then, we use local, deformable compartment shape registration using MRF-based free-form deformations. We validated our results using aCC motorneuron image stacks from larva Drosophila, at multiple developmental instances and different spatial resolutions.

Original languageEnglish (US)
Title of host publication2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018
PublisherIEEE Computer Society
Number of pages5
ISBN (Electronic)9781538636367
StatePublished - May 23 2018
Event15th IEEE International Symposium on Biomedical Imaging, ISBI 2018 - Washington, United States
Duration: Apr 4 2018Apr 7 2018

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452


Other15th IEEE International Symposium on Biomedical Imaging, ISBI 2018
Country/TerritoryUnited States


  • Free-form deformations
  • Markov Random Fields
  • Neuron morphology
  • Registration
  • Segmentation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging


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