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Content based modified reaction-diffusion equation for modeling tumor growth of low grade glioma

机译:基于含量的改性反应扩散方程,用于肿瘤生长低等级神经胶质瘤

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This paper presents a content based modified reaction diffusion (RD) equation for modeling glioma growth. The reaction diffusion equation is modified by a weighted parameter that measures the white matter proportion in a small window. Given two MRI time-points scans of the same patient, the manually segmented tumor of the first scan is used as an initial seed to the proposed method while the second scan is used as the ground truth to measure the accuracy of the simulated results. For healthy tissues segmentation around the initial seed, spatial fuzzy C-means algorithm that accounts for neighborhood information of the image is used. As a proof of concept, the proposed method is tested on one low grade glioma case with 7 month difference between the two scans. The preliminary results of the modified RD equation show higher accuracy as compared with the standard RD equation.
机译:本文介绍了一种基于含量的用于建模胶质瘤生长的改性反应扩散(RD)方程。 反应扩散方程由测量小窗口中的白质比测量的加权参数进行修改。 考虑到同一患者的两个MRI时间点扫描,第一扫描的手动分段肿瘤用作所提出的方法的初始种子,而第二扫描用作衡量模拟结果的准确性的原始种子。 对于初始种子周围的健康组织分割,使用用于占据图像的邻域信息的空间模糊C均值算法。 作为概念证明,所提出的方法在一个低级胶质瘤壳体上进行测试,两次扫描之间的7个月差异。 与标准RD方程相比,改进的RD方程的初步结果显示出更高的精度。

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