caa a22 4500 397569858 CHVBK 20180308164838.0 cr unu---uuuuu 161202e199608 xx s 000 0 eng 10.1093/oxfordjournals.jmicro.a023446 doi (NATIONALLICENCE)oxford-10.1093/oxfordjournals.jmicro.a023446 Image Area Extraction of Biological Objects from a Thin Section Image by Statistical Texture Analysis [Elektronische Daten] [Norio Baba, Norihiko Ichise, Toshiyuki Tanaka] The statistical method in texture image analysis was applied to area extraction of biological objects from thin section electron microscope images. Four standard estimators defined from the gray level co-occurrence matrix, called ‘inverse difference moment,' ‘angular second moment,' ‘entropy' and ‘contrast,' were especially examined using a test pattern consisting of 6 artificial textures and to practical biological thin section images. In the examination on the test pattern, among the estimators the ‘contrast' discriminated all textures, but differences of some texture feature levels were small. To clearly discriminate textures, a modified estimator combining ‘angular second moment' and ‘contrast' was devised. As a result it discriminated all better than the ‘contrast.' Electron microscope images used for the image processing are yeast morphological ones showing spherical autophagic bodies in the vacuole. Although the four standard estimators discriminated many organelles, they could not exactly extract images of the autophagic body. However, the modified estimator was able to extract all autophagic bodies from the vacuole image area except for minor points, some of which were not clearly detected by man observation. It was found out that the texture analysis-based method can be used to discriminate slight differences between image textures due to spatial staining granularity. © 1996 Oxford University Press Full-length Papers nationallicence texture analysis nationallicence gray level co-occurrence matrix nationallicence spatial gray level dependence method nationallicence image segmentation nationallicence thin section image nationallicence Baba Norio Department of Electrical Engineering, Kogakuin University, Nishishinjuku 1-24-2, Shinjuku-ku, Tokyo, 163-91 Japan aut Ichise Norihiko Department of Electrical Engineering, Kogakuin University, Nishishinjuku 1-24-2, Shinjuku-ku, Tokyo, 163-91 Japan aut Tanaka Toshiyuki Department of Electrical Engineering, Kogakuin University, Nishishinjuku 1-24-2, Shinjuku-ku, Tokyo, 163-91 Japan aut Microscopy Oxford University Press 45/4(1996-08), 298-306 0022-0744 45:4<298 1996 45 jmicro https://doi.org/10.1093/oxfordjournals.jmicro.a023446 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1093/oxfordjournals.jmicro.a023446 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Baba Norio Department of Electrical Engineering, Kogakuin University, Nishishinjuku 1-24-2, Shinjuku-ku, Tokyo, 163-91 Japan aut NATIONALLICENCE 700 1- Ichise Norihiko Department of Electrical Engineering, Kogakuin University, Nishishinjuku 1-24-2, Shinjuku-ku, Tokyo, 163-91 Japan aut NATIONALLICENCE 700 1- Tanaka Toshiyuki Department of Electrical Engineering, Kogakuin University, Nishishinjuku 1-24-2, Shinjuku-ku, Tokyo, 163-91 Japan aut NATIONALLICENCE 773 0- Microscopy Oxford University Press 45/4(1996-08), 298-306 0022-0744 45:4<298 1996 45 jmicro Metadata rights reserved CC BY-NC-4.0 http://creativecommons.org/licenses/by-nc/4.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-oxford