In radiation therapy, precise dose distribution is essential for minimizing damage to normal tissues. Gafchromic EBT3 film is widely used to assure the quality of two-dimensional dosimetry but requires frequent recalibrations due to changes in sensitivity over time. This study presents a new calibration method using a Keras-based generalized additive neural network (GANN) to address film aging. EBT3 films from four lots were calibrated with a 6 MV photon beam and scanned on Epson scanners. The GANN method achieved percentage differences between calibrated and delivered doses within 5%, comparable to traditional recalibration methods, with an overall uncertainty of approximately 2%. It demonstrated improved stability and accuracy, significantly reducing the need for frequent recalibrations and providing a robust solution for long-term film dosimetry.
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Adaptive calibration of Gafchromic EBT3 film using generalized additive neural networks.
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Medical Physics and Informatics Laboratory of Electronics Engineering, National Kaohsiung University of Sciences and Technology, Kaohsiung, 80778, Taiwan, ROC.
In radiation therapy, precise dose distribution is essential for minimizing damage to normal tissues. Gafchromic EBT3 film is widely used to assure the quality of two-dimensional dosimetry but requires frequent recalibrations due to changes in sensitivity over time. This study presents a new calibration method using a Keras-based generalized additive neural network (GANN) to address film aging.
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