Kermanshah University of Technology

Research

Title	Prediction of the thickness of the compensator filter in radiation therapy using computational intelligence
Type	Article
Keywords	—
Researchers	vahab dehlaghi، Mostafa Taghipour، Abbas Haghparast، Gholam Hossein Roshani، Abbas Rezaei، Sajjad Pashootan Shayesteh,، Ayoub Adineh-Vand، Gholam Reza Karimi

Abstract

In this study, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) are investigated to predict the thickness of the compensator filter in radiation therapy. In the proposed models, the input parameters are field size (S), off-axis distance, and relative dose (D/D0), and the output is the thickness of the compensator. The obtained results show that the proposed ANN and ANFIS models are useful, reliable, and cheap tools to predict the thickness of the compensator filter in intensity-modulated radiation therapy.

Abbas Rezaei

Research

Abstract