(Sunday, 7/29/2018) 3:00 PM - 6:00 PM
Room: Exhibit Hall
Purpose: GAFChromic EBT-3 �lms ( International Specialty Products, Wayne, NJ, USA) is widely used for verification of radiation dose. EBT-3 has great spatial resolution, tissue equivalent and no energy dependence for high energy. The calibration curve of EBT-3 film should be established. Because the various dose-response is observed in the different lot numbers of the film and radiation facilities.In this study, we use machine learning method to build the calibration curve of radiochromic EBT-3 film, and then compare with the calibration curve of FilmQA pro (Ashland, US, 2016).
Methods: Machine learning: Tensorflow database was used in this study to build calibration model. Three pixel values were selected by the multi-dimensional tensor features as follows red, blue and green. In addition, optical density, field size and resolution were evaluated.Measurement: Radiochromic EBT-3 film was placed at 5 cm depth in a solid water phantom, and field size was 5×5. The films were irradiated with a 6 MV photon beam using Varian Clinac® iX System linear accelerator. The films were exposed to radiation dose of 50, 100, 200, 300, 400, 500, 700, 1000 cGy . Epson® Expression® 11000XL scanner was used to detect the density of all films using three spatial resolution of 48, 72, 144 dpi .Comparison:The calibration curve of EBT-3 film was analyzed using FilmQA pro software, and that was compared with the prediction curve of machine learning method.
Results: In this study, EBT-3 film dosimetry was calculated by FilmQA pro software and that was evaluated and analyzed using machine learning method .
Conclusion: The calibration curves were similar between FilmQA pro software and machine learning method analyses. The features of EBT-3 film dosimetry system in machine learning method were successfully verified. Therefore, training data and feature were improved the accuracy of the model in the future.
Keywords
Absolute Dosimetry, Dose Response
Taxonomy
TH- External beam- photons: Quality Assurance - Linear accelerator
Contact Email
