Diffusion Correction in Fricke Hydrogel Dosimeters: A Deep Learning Approach with 2D and 3D Physics-Informed Neural Network Models

In this work an innovative approach was developed to address a significant challenge in the field of radiation dosimetry: the accurate measurement of spatial dose distributions using Fricke gel dosimeters. Hydrogels are widely used in radiation dosimetry due to their ability to simulate the tissue-e...

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Hlavní autoři:	Mattia Romeo, Grazia Cottone, Maria Cristina D’Oca, Antonio Bartolotta, Salvatore Gallo, Roberto Miraglia, Roberta Gerasia, Giuliana Milluzzo, Francesco Romano, Cesare Gagliardo, Fabio Di Martino, Francesco d’Errico, Maurizio Marrale
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2024-08-01
Edice:	Gels
Témata:	gel dosimetry Fricke gels diffusion artificial intelligence PINN
On-line přístup:	https://www.mdpi.com/2310-2861/10/9/565
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