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Texture descriptions and classification for pathological analysis of cancerous colonic mucosa

机译:癌性结肠黏膜病理分析的质地描述和分类

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Image analysis for the classification of normal and cancerous colonic mucosa is reported. Pathology samples were taken from human colon mucosa, and 44 normal and 58 cancer images captured to computer via an optical microscope with a CCD camera. Texture analysis was performed using fractal dimension, entropy and correlation. Using non-parametric classification, fractal dimension improved the classification accuracy from 88% to 94% in comparison with the combined entropy and correlation analysis.
机译:报道了对正常和癌性结肠粘膜进行分类的图像分析。病理样本取自人结肠粘膜,并通过带有CCD相机的光学显微镜将44幅正常图像和58幅癌症图像捕获到计算机中。使用分形维数,熵和相关性进行纹理分析。与结合熵和相关性分析相比,使用非参数分类,分形维数将分类精度从88%提高到94%。

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