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Texture based characterization and automatic diagnosis of the abdominal tumors from ultrasound images using third order GLCM features

机译:三阶GLCM特征基于纹理的特征及腹部肿瘤的自动诊断

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The frequency of the cancer cases is continuously increasing. The golden standard for the malignant tumor diagnosis is the biopsy, but this is often a dangerous method. We aim to develop computerized, non-invasive techniques for the automatic diagnosis of the abdominal malignant tumors, based on ultrasound images. We take into consideration the hepatocellular carcinoma (HCC) and the colo-rectal tumors for this purpose. The texture is an important property of the internal organ tissues, providing subtle information about the pathology. We previously defined the textural model of HCC, consisting in the exhaustive set of the relevant textural features, appropriate for HCC characterization and in their specific values. In this work, we analyze the role that the third order Gray Level Cooccurrence Matrix (GLCM) has on the characterization and automatic diagnosis of the abdominal malignant tumors. We also determine the best spatial relation between the pixels that leads to the highest performances.
机译:癌症病例的频率不断增加。恶性肿瘤诊断的黄金标准是活组织检查,但这通常是一种危险的方法。我们的目标是基于超声图像开发用于自动诊断腹部恶性肿瘤的计算机化的非侵入性技巧。我们考虑了肝细胞癌(HCC)和COLO-直肠肿瘤的目的。纹理是内部器官组织的重要特性,提供有关病理学的微妙信息。我们之前定义了HCC的纹理模型,包括穷举的相关纹理特征,适用于HCC表征和特定值。在这项工作中,我们分析了三阶灰度级Cooccurrence矩阵(GLCM)对腹部恶性肿瘤的表征和自动诊断的作用。我们还确定导致最高性能的像素之间的最佳空间关系。

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