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Patient specific dose estimation is traditionally calculated though Monte-Carlo methods but not performed during CT image acquisition due to long computation times. We propose the implementation of a NN to perform patient specific dose estimation that can be performed alongside the CT acquisition due to the reduction in computation time. This is achieved by first performing MC simulations and then training the NN to replicate these predictions. The NN shows promise with a high degree of total cranial dose accuracy between the predictions and ground truth with a standard deviation of less than ±0.5 mGy.
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Thomas Holmes, Roozbeh Tarighati Rasekhi, Sara Shirazi, Erica Riedesel, Amir Pourmorteza, "Pediatric CT cranial radiation dose estimation using deep learning," Proc. SPIE 12031, Medical Imaging 2022: Physics of Medical Imaging, 120312L (4 April 2022); https://doi.org/10.1117/12.2612581