Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1880098 | Medical Dosimetry | 2015 | 5 Pages |
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.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Radiation
Authors
Vahab Ph.D., Mostafa M.S., Abbas Ph.D., Gholam Hossein Ph.D., Abbas Ph.D., Sajjad Pashootan M.S., Ayoub Ph.D., Gholam Reza Ph.D.,