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Evaluation of malignancy in tumors of the central nervous system using fractal dimension

机译:分形维数评价中枢神经系统肿瘤恶性肿瘤

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We propose the use of the concepts of fractal dimension and digital image processing, as a possible methodology to characterize the degree of malignancy of neoplastic structures located in the central nervous system. The images were detected by MRI techniques including proton density, T/sub 1/, and T/sub 2/ images. Malignant lesions (Gliomas) were compared with benign ones (cysts). The correlation dimension, Lyapunov exponents and information dimension were used as the relevant geometrical properties to characterize the irregular edge present in a particular structure. The edge was obtained by means of an edge detector operator and afterwards a codification procedure based on Fourier descriptors was used to generate a numerical array or time series. The analysis of the processed images revealed that the relevant geometrical properties exhibit a different behavior in the case of gliomas compared to cystic lesions, a fact that can be used by the physician as an auxiliary tool to evaluate the malignancy of neoplastic structures in the brain.
机译:我们提出了使用分形维数和数字图像处理的概念,作为表征位于中枢神经系统中的肿瘤结构的恶性程度的可能方法。通过MRI技术检测图像,包括质子密度,T / SUB 1 /和T / SUB 2 /图像。将恶性病变(Gliomas)与良性人(囊肿)进行比较。相关尺寸,Lyapunov指数和信息尺寸用作相关的几何特性,以表征特定结构中存在的不规则边缘。通过边缘检测器操作器获得边缘,然后基于傅立叶描述符的编码过程用于生成数值阵列或时间序列。处理后的图像的分析显示,与囊状病变相比,相关的几何特性在胶质瘤的情况下表现出不同的行为,该事实可以由医生作为辅助工具来评估大脑中肿瘤结构恶性肿瘤的事实。

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