Image processing and reconstruction of cultured neuron skeletons

  • Authors:

  • Donggang Yu;Tuan D. Pham;Hong Yan;Jesse S. Jin;Suhuai Luo;Denis I. Crane

  • Affiliations:

  • School of Desigh, Communication and Information Technology, The University of Newcastle, Callaghan, NSW 2308, Australia;(Correspd. E-mail: t.pham@adfa.edu.au) ADFA School of Information Technology and Electrical Engineering, The University of New South Wales, Canberra, ACT 2600, Australia;Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong and School of Electrical and Information Engineering, University of Sydney, NSW 2006, Australia;School of Desigh, Communication and Information Technology, The University of Newcastle, Callaghan, NSW 2308, Australia;School of Desigh, Communication and Information Technology, The University of Newcastle, Callaghan, NSW 2308, Australia;School of Biomolecular and Biomedical Science and Eskitis Institute for Cell and Molecular Therapies, Griffith University, Nathan, Qld 4111, Australia

  • Venue:
  • International Journal of Hybrid Intelligent Systems - Computational Models for Life Sciences
  • Year:
  • 2008

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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.