Luca Eugeni
Improving validation of Instadose dosimeters using machine learning algorithms.
Rel. Raffaella Testoni, Federica Roberto. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Energetica E Nucleare, 2024
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Abstract
Dosimetry represents a key aspect in the radioprotection field for nuclear related activities: people working with ionising radiation need to monitor their exposure to be able to optimise their doses and to keep them below the dose limits. Such dosimeters are provided by approved dosimetry services, like SCK CEN. These dosimetry services need to prove that the doses they measure are correct. In this process, the validation of the personal dosimeter results is of major importance. The validation process ensures a reliable measurement of the personal dose equivalent and guarantees the correct operation of the dosimeter. In this project the focus is on Instadose dosimeters, which is a novel type of hybrid personal dosimeter.
SCK nuclear research centre provides currently ~ 2000 Instadose dosimeters to different costumers, such as hospitals and companies
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