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Segmentation of Neuronal Axons in Brainbow Images

  • Kim, Tae-Yun (Biomedical Engineering Branch, National Cancer Center) ;
  • Kang, Mi-Sun (Department of Computer Science and Engineering, Ewha Womans University) ;
  • Kim, Myoung-Hee (Department of Computer Science and Engineering, Ewha Womans University) ;
  • Choi, Heung-Kook (Department of Computer Engineering, UHRC, Inje University)
  • Received : 2012.07.18
  • Accepted : 2012.09.17
  • Published : 2012.12.31

Abstract

In neuroscientific research, image segmentation is one of the most important processes. The morphology of axons plays an important role for researchers seeking to understand axonal functions and connectivity. In this study, we evaluated the level set segmentation method for neuronal axons in a Brainbow confocal microscopy image. We first obtained a reconstructed image on an x-z plane. Then, for preprocessing, we also applied two methods: anisotropic diffusion filtering and bilateral filtering. Finally, we performed image segmentation using the level set method with three different approaches. The accuracy of segmentation for each case was evaluated in diverse ways. In our experiment, the combination of bilateral filtering with the level set method provided the best result. Consequently, we confirmed reasonable results with our approach; we believe that our method has great potential if successfully combined with other research findings.

Keywords

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