3-D centerline extraction of axons in microscopic stacks for the study of motor neuron behavior in developing muscles

Ranga Srinivasan, Xiaobo Zhou, Eric Miller, Ju Lu, Jeff Lichtman, Stephen T. Wong

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

3 Scopus citations

Abstract

This paper presents a new algorithm for extracting the centerlines of the axons from 3-D data stacks collected from a laser scanning confocal microscope. Recovery of neuronal structure from such datasets is critical for quantitatively addressing a range of basic biological questions such as the manner in which the branching pattern of motor neurons change during synapse elimination. The presence of artifacts in the crosssectional images such as blurred boundaries and non-uniform intensities, makes the process of centerline extraction rather challenging. Although many methods exist in practice today, they are either error-prone or involve manual interaction to a large extent, when applied to this particular problem. We propose a robust probabilistic region growing algorithm to extract the centers from the datasets with minimal user interaction.

Original languageEnglish (US)
Title of host publication2007 4th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages93-96
Number of pages4
DOIs
StatePublished - Nov 27 2007
Event2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07 - Arlington, VA, United States
Duration: Apr 12 2007Apr 15 2007

Other

Other2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07
CountryUnited States
CityArlington, VA
Period4/12/074/15/07

Keywords

  • Crossover
  • Maximum intensity projection
  • Region growing
  • Segmentation
  • Watershed

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Medicine(all)

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