Research Info

Title	Prediction of the thickness of the compensator filter in radiation therapy using computational intelligence
Type	JournalPaper
Keywords	Not Registered!
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.
Researchers	Gholam Reza Karimi (Not In First Six Researchers), Ayoub Adineh-Vand (Not In First Six Researchers), Sajjad Pashootan Shayesteh, (Not In First Six Researchers), Abbas Haghparast (Third Researcher), Mostafa Taghipour (Second Researcher), vahab dehlaghi (First Researcher), Abbas Rezaei (Fifth Researcher), Gholam Hossein Roshani (Fourth Researcher)