@inbook{1ee7a86f881e4ad6b532892e5a242d8f,
title = "Cancer prediction modeling from volumetric data",
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.",
keywords = "Fister-panetta model, Prediction, Tumor growth",
author = "Marius Paltanea and Sabin Tabirca and Chen, \{Yin Jie\} and Mark Tangney",
year = "2009",
doi = "10.1109/SYNASC.2009.36",
language = "English",
isbn = "9780769539645",
series = "SYNASC 2009 - 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing",
pages = "162--167",
booktitle = "SYNASC 2009 - 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing",
note = "11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2009 ; Conference date: 26-09-2009 Through 29-09-2009",
}
