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Deep Learning for Pediatric sCT in Radiotherapy by Vũ Huy is a document available to read on EtoBox.

What is Deep Learning for Pediatric sCT in Radiotherapy about?

This study evaluates the feasibility of generating synthetic computed tomography (sCT) images from magnetic resonance imaging (MRI) for pediatric brain radiotherapy using deep learning techniques. The research involved 60 pediatric patients and demonstrated that multi-plane sCT generation using conditional generative adversarial networks (cGANs) can achieve accurate dose calculations for both photon and proton therapies. Results indicated a mean absolute error of 61 ± 14 HU and high pass rates for dosimetri

Author

Vũ Huy

Language

EN