A deep learning algorithm to generate synthetic computed tomography images for brain treatments from 0.35 T magnetic resonance imaging

A deep learning algorithm to generate synthetic computed tomography images for brain treatments from 0.35 T magnetic resonance imaging

Background and Purpose: The development of Magnetic Resonance Imaging (MRI)-only Radiotherapy (RT) represents a significant advancement in the field. This study introduces a Deep Learning (DL) algorithm designed to quickly generate synthetic CT (sCT) images from low-field MR images in the brain, an...

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Bibliographic Details
Main Authors: Luca Vellini, Flaviovincenzo Quaranta, Sebastiano Menna, Elisa Pilloni, Francesco Catucci, Jacopo Lenkowicz, Claudio Votta, Michele Aquilano, Andrea D’Aviero, Martina Iezzi, Francesco Preziosi, Alessia Re, Althea Boschetti, Danila Piccari, Antonio Piras, Carmela Di Dio, Alessandro Bombini, Gian Carlo Mattiucci, Davide Cusumano
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Physics and Imaging in Radiation Oncology
Subjects:
Artificial intelligence
Synthetic CT
MRI-only workflow
GAN
Online Access:http://www.sciencedirect.com/science/article/pii/S2405631625000132
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http://www.sciencedirect.com/science/article/pii/S2405631625000132

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