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Updated: Mar 6, 2026
Micron-scale Resolution Optical Tomography of Entire Mouse Brains with Confocal Light Sheet Microscopy
Published on: October 8, 2013
Gray-level co-occurrence matrix analysis of several cell types in mouse brain using resolution-enhanced photothermal
Takayoshi Kobayashi1, Durga Sundaram2, Kazuaki Nakata3
1University of Electro-Communications, Advanced Ultrafast Laser Research Center, Chofu, Tokyo, JapanbJapan Science and Technology Agency, Core Research for Evolutional Science and Technology, K's Gobancho, Chiyoda-ku, Tokyo, JapancNational Chiao-Tung University, Department of Electrophysics, Hsinchu, TaiwandOsaka University, Institute of Laser Engineering, Suita, Osaka, Japan.
This study introduces the gray-level co-occurrence matrix (GLCM) method for analyzing intracellular structures in mouse brain cells. The inverse difference moment (IDM) and angular second moment (ASM) proved most effective for distinguishing cell types.
Area of Science:
- Neuroscience
- Biophysics
- Image Analysis
Background:
- Characterizing intracellular structures is crucial for understanding cell function.
- Previous methods lacked detailed quantitative analysis of cellular texture.
- Resolution-enhanced photothermal imaging offers high-resolution cellular images.
Purpose of the Study:
- To apply the gray-level co-occurrence matrix (GLCM) method for the first time to quantify intracellular structures.
- To identify the most suitable GLCM texture parameters for differentiating various mouse brain cell types.
- To correlate texture features with specific neuronal and glial cell populations.
Main Methods:
- Utilized resolution-enhanced photothermal imaging to capture high-resolution cell images.
- Applied the gray-level co-occurrence matrix (GLCM) method to extract five texture features: correlation, contrast, angular second moment (ASM), inverse difference moment (IDM), and entropy.
- Analyzed texture parameters across five distinct mouse brain cell types: pyramidal neurons, basal nucleus glial cells (BGl), dentate gyrus granule cells, cerebellar Purkinje cells, and cerebellar granule cells.
Main Results:
- Texture parameters varied based on pixel distance in the GLCM analysis.
- The inverse difference moment (IDM) was identified as the most suitable parameter for pyramidal neurons, BGl cells, dentate gyrus granule cells, cerebellar Purkinje cells, and cerebellar granule cells.
- The angular second moment (ASM) was found to be the most appropriate parameter for basal nucleus neurons.
Conclusions:
- The GLCM method provides a robust quantitative approach for intracellular structure analysis.
- Specific GLCM parameters (IDM and ASM) can effectively differentiate between various mouse brain cell types.
- This technique enhances our ability to characterize cellular heterogeneity in the brain.
