University 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.
University of Electro-Communications, Advanced Ultrafast Laser Research Center, Chofu, Tokyo, JapaneSastra University, Tirumalaisamudram, Thanjavur, Tamil Nadu, India.
J Biomed Opt. 2017 Mar 1;22(3):36011. doi: 10.1117/1.JBO.22.3.036011.
Qualifications of intracellular structure were performed for the first time using the gray-level co-occurrence matrix (GLCM) method for images of cells obtained by resolution-enhanced photothermal imaging. The GLCM method has been used to extract five parameters of texture features for five different types of cells in mouse brain; pyramidal neurons and glial cells in the basal nucleus (BGl), dentate gyrus granule cells, cerebellar Purkinje cells, and cerebellar granule cells. The parameters are correlation, contrast, angular second moment (ASM), inverse difference moment (IDM), and entropy for the images of cells of interest in a mouse brain. The parameters vary depending on the pixel distance taken in the analysis method. Based on the obtained results, we identified that the most suitable GLCM parameter is IDM for pyramidal neurons and BGI, granule cells in the dentate gyrus, Purkinje cells and granule cells in the cerebellum. It was also found that the ASM is the most appropriate for neurons in the basal nucleus.
首次使用灰度共生矩阵 (GLCM) 方法对经分辨率增强光热成像获得的细胞图像进行细胞内结构的定量分析。GLCM 方法已被用于提取 5 种纹理特征参数，用于分析小鼠脑内的 5 种不同类型的细胞，包括基底核中的锥体神经元和胶质细胞（BGl）、齿状回颗粒细胞、小脑浦肯野细胞和小脑颗粒细胞。这些参数是基于分析方法中所取像素距离的不同，针对感兴趣的小鼠脑内细胞图像的相关性、对比度、角二阶矩 (ASM)、逆差矩 (IDM) 和熵进行计算。根据获得的结果，我们确定最适合的 GLCM 参数是 IDM，它可用于分析锥体神经元和 BGl、齿状回颗粒细胞、浦肯野细胞和小脑颗粒细胞。我们还发现 ASM 最适合用于基底核内的神经元。
