A Convenient Semi-Automatic Method for Analyzing Brain Sections: Registration, Segmentation and Cell Counting

  • ZHU Xu-tao ,
  • HE Xiao-bin ,
  • LIU Yue ,
  • WEN Peng-jie ,
  • WANG Li ,
  • ZHANG Zhi-jian ,
  • XU Fu-qiang
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  • 1. Center for Brain Science, CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan(Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences), Wuhan 430071, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2017-12-05

  Online published: 2018-01-08

Abstract

Quantitative analyses of molecular expression, cell counts and neural network connections among different brain regions are essential in brain science research. Based on Paxinos and Franklin's the Mouse Brain in Stereotaxic Coordinates (Ⅱ) and public image processing software such as Photoshop and ImageJ, we developed a convenient method for semi-automatic segmentation and cell counting on brain sections. A standard template for brain region segmentation was first obtained from the Paxinos and Franklin's mouse brain atlas. Photoshop was then used to transform the standard template semi-automatically into the space of brain sections, yielding masks of segmented brain regions. Finally, ImageJ was used to analyze the data in different brain regions. This method is useful for immunohistochemical and neuron distribution pattern analyses, as well as neural network labelling studies. The method does not require expensive commercial image analysis software, and is also easy to implement and use.

Cite this article

ZHU Xu-tao , HE Xiao-bin , LIU Yue , WEN Peng-jie , WANG Li , ZHANG Zhi-jian , XU Fu-qiang . A Convenient Semi-Automatic Method for Analyzing Brain Sections: Registration, Segmentation and Cell Counting[J]. Chinese Journal of Magnetic Resonance, 2018 , 35(2) : 133 -140 . DOI: 10.11938/cjmr20172608

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