Chapter

Knowledge-Based Systems in Biomedicine and Computational Life Science

Volume 450 of the series Studies in Computational Intelligence pp 43-78

Image Processing and Reconstruction of Cultured Neuron Skeletons

  • Donggang YuAffiliated withADFA School of Information Technology and Electrical Engineering, The University of New South WalesSchool of Desigh, Communication and Information Technology, The University of Newcastle
  • , Tuan D. PhamAffiliated withADFA School of Information Technology and Electrical Engineering, The University of New South Wales
  • , Jesse S. JinAffiliated withSchool of Desigh, Communication and Information Technology, The University of Newcastle
  • , Suhuai LuoAffiliated withSchool of Desigh, Communication and Information Technology, The University of Newcastle
  • , Hong YanAffiliated withDepartment of Electronic Engineering, City University of Hong KongSchool of Electrical and Information Engineering, University of Sydney
  • , Denis I. CraneAffiliated withSchool of Biomolecular and Biomedical Science, Griffith UniversityEskitis Institute for Cell and Molecular Therapies, Griffith University

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Abstract

One approach to investigating neural death is through systematic studies of the changing morphology of cultured brain neurons in response to cellular challenges. Image segmentation and neuron skeleton reconstruction methods developed to date to analyze such changes have been limited by the low contrast of cells. In this paper we present new algorithms that successfully circumvent these problems. The binary method is based on logical analysis of grey and distance difference of images. The spurious regions are detected and removed through use of a hierarchical window filter. The skeletons of binary cell images are extracted. The extension direction and connection points of broken cell skeletons are automatically determined, and broken neural skeletons are reconstructed. The spurious strokes are deleted based on cell prior knowledge. The reconstructed skeletons are processed furthermore by filling holes, smoothing and extracting new skeletons. The final constructed neuron skeletons are analyzed and calculated to find the length and morphology of skeleton branches automatically. The efficacy of the developed algorithms is demonstrated here through a test of cultured brain neurons from newborn mice.

Keywords

Neuron cell image image segmentation grey and distance difference filtering window neuron skeleton skeleton reconstruction skeleton branch