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

• Main Authors: ZHU Xu-tao, HE Xiao-bin, LIU Yue, WEN Peng-jie, WANG Li, ZHANG Zhi-jian, XU Fu-qiang
• Format: Article
• Language: zho
• Published: Science Press 2018-06-01
• Series: Chinese Journal of Magnetic Resonance
• Subjects: neural network; virus labelling; brain section segmentation; cell counting
• Online Access: http://121.43.60.238/bpxzz/EN/10.11938/cjmr20172608#
• ISSN: 1000-4556; 1000-4556

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.