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Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices Based on Ultrasound Images

机译:基于超声图像的上位共生矩阵对腹部肿瘤的表征和识别

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摘要

The noninvasive diagnosis of the malignant tumors is an important issue in research nowadays. Our purpose is to elaborate computerized, texture-based methods for performing computer-aided characterization and automatic diagnosis of these tumors, using only the information from ultrasound images. In this paper, we considered some of the most frequent abdominal malignant tumors: the hepatocellular carcinoma and the colonic tumors. We compared these structures with the benign tumors and with other visually similar diseases. Besides the textural features that proved in our previous research to be useful in the characterization and recognition of the malignant tumors, we improved our method by using the grey level cooccurrence matrix and the edge orientation cooccurrence matrix of superior order. As resulted from our experiments, the new textural features increased the malignant tumor classification performance, also revealing visual and physical properties of these structures that emphasized the complex, chaotic structure of the corresponding tissue.
机译:恶性肿瘤的无创诊断是当今研究的重要课题。我们的目的是建立仅基于超声图像的信息,以计算机化,基于纹理的方法进行这些肿瘤的计算机辅助表征和自动诊断。在本文中,我们考虑了一些最常见的腹部恶性肿瘤:肝细胞癌和结肠肿瘤。我们将这些结构与良性肿瘤以及其他视觉相似的疾病进行了比较。除了在先前研究中证明对恶性肿瘤的表征和识别有用的纹理特征外,我们还通过使用高级灰度共生矩阵和边缘方向共生矩阵改进了我们的方法。由于我们的实验,新的纹理特征提高了恶性肿瘤的分类性能,还揭示了这些结构的视觉和物理特性,从而强调了相应组织的复杂,混乱的结构。

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