Cancer Prediction Modeling from Volumetric Data

Marius Paltanea, S. Tabirca, Y. J. Chen, M. Tangney
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引用次数: 2

Abstract

This paper introduces a method for cancer prediction based on the Fister-Panetta (FP) model for cancer growth.The FP equation includes a component for the tumor growth which describes its natural evolution without any treatment.The second component of the FP equation is represented by the contribution of the treatment scheme. Our prediction uses these two components to predict the evolution of the tumor in the near future. The prediction model uses the real information about the tumor growth in this two cases to find the best mathematical approximation with the FP equation. Then this equation is used to predict the evolution in the near future of the tumor.
基于体积数据的癌症预测建模
本文介绍了一种基于肿瘤生长的Fister-Panetta (FP)模型的肿瘤预测方法。FP方程包括肿瘤生长的一个组成部分,它描述了肿瘤在没有任何治疗的情况下的自然演变。FP方程的第二个组成部分由处理方案的贡献表示。我们的预测使用这两个组成部分来预测肿瘤在不久的将来的演变。预测模型利用这两种情况下肿瘤生长的真实信息,用FP方程找到最佳的数学近似。然后用这个方程来预测肿瘤在不久的将来的演变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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