A Convenient Semi-Automatic Method for Analyzing Brain Sections: Registration, Segmentation and Cell Counting
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...
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doaj-93f74a337e074902a16e0938d217049c2020-11-25T01:07:20ZzhoScience PressChinese Journal of Magnetic Resonance1000-45561000-45562018-06-0135213314010.11938/cjmr20172608A Convenient Semi-Automatic Method for Analyzing Brain Sections: Registration, Segmentation and Cell CountingZHU Xu-tao0HE Xiao-bin1LIU Yue2WEN Peng-jie3WANG Li4ZHANG Zhi-jian5XU Fu-qiang61. 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, ChinaCenter 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, ChinaCenter 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, China1. 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, ChinaCenter 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, ChinaCenter 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, China1. 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, ChinaQuantitative 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. http://121.43.60.238/bpxzz/EN/10.11938/cjmr20172608#neural networkvirus labellingbrain section segmentationcell counting |
collection |
DOAJ |
language |
zho |
format |
Article |
sources |
DOAJ |
author |
ZHU Xu-tao HE Xiao-bin LIU Yue WEN Peng-jie WANG Li ZHANG Zhi-jian XU Fu-qiang |
spellingShingle |
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 Chinese Journal of Magnetic Resonance neural network virus labelling brain section segmentation cell counting |
author_facet |
ZHU Xu-tao HE Xiao-bin LIU Yue WEN Peng-jie WANG Li ZHANG Zhi-jian XU Fu-qiang |
author_sort |
ZHU Xu-tao |
title |
A Convenient Semi-Automatic Method for Analyzing Brain Sections: Registration, Segmentation and Cell Counting |
title_short |
A Convenient Semi-Automatic Method for Analyzing Brain Sections: Registration, Segmentation and Cell Counting |
title_full |
A Convenient Semi-Automatic Method for Analyzing Brain Sections: Registration, Segmentation and Cell Counting |
title_fullStr |
A Convenient Semi-Automatic Method for Analyzing Brain Sections: Registration, Segmentation and Cell Counting |
title_full_unstemmed |
A Convenient Semi-Automatic Method for Analyzing Brain Sections: Registration, Segmentation and Cell Counting |
title_sort |
convenient semi-automatic method for analyzing brain sections: registration, segmentation and cell counting |
publisher |
Science Press |
series |
Chinese Journal of Magnetic Resonance |
issn |
1000-4556 1000-4556 |
publishDate |
2018-06-01 |
description |
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. |
topic |
neural network virus labelling brain section segmentation cell counting |
url |
http://121.43.60.238/bpxzz/EN/10.11938/cjmr20172608# |
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