[HTML][HTML] Overview of artificial intelligence-based applications in radiotherapy: Recommendations for implementation and quality assurance

L Vandewinckele, M Claessens, A Dinkla… - Radiotherapy and …, 2020 - Elsevier
Artificial Intelligence (AI) is currently being introduced into different domains, including
medicine. Specifically in radiation oncology, machine learning models allow automation and …

Deep learning based synthetic‐CT generation in radiotherapy and PET: a review

MF Spadea, M Maspero, P Zaffino, J Seco - Medical physics, 2021 - Wiley Online Library
Abstract Recently, deep learning (DL)‐based methods for the generation of synthetic
computed tomography (sCT) have received significant research attention as an alternative to …

Deep learning methods to generate synthetic CT from MRI in radiotherapy: A literature review

M Boulanger, JC Nunes, H Chourak, A Largent, S Tahri… - Physica Medica, 2021 - Elsevier
Purpose In radiotherapy, MRI is used for target volume and organs-at-risk delineation for its
superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the …

[HTML][HTML] Deep learning based synthesis of MRI, CT and PET: Review and analysis

S Dayarathna, KT Islam, S Uribe, G Yang, M Hayat… - Medical Image …, 2023 - Elsevier
Medical image synthesis represents a critical area of research in clinical decision-making,
aiming to overcome the challenges associated with acquiring multiple image modalities for …

MR-guided proton therapy: a review and a preview

A Hoffmann, B Oborn, M Moteabbed, S Yan… - Radiation …, 2020 - Springer
Background The targeting accuracy of proton therapy (PT) for moving soft-tissue tumours is
expected to greatly improve by real-time magnetic resonance imaging (MRI) guidance. The …

[HTML][HTML] Deep learning-based synthetic CT generation for paediatric brain MR-only photon and proton radiotherapy

M Maspero, LG Bentvelzen, MHF Savenije… - Radiotherapy and …, 2020 - Elsevier
Abstract Background and Purpose To enable accurate magnetic resonance imaging (MRI)-
based dose calculations, synthetic computed tomography (sCT) images need to be …

Comparison of CBCT based synthetic CT methods suitable for proton dose calculations in adaptive proton therapy

A Thummerer, P Zaffino, A Meijers… - Physics in Medicine …, 2020 - iopscience.iop.org
In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-
beam computed tomography (CBCT) imaging, which is routinely acquired for patient …

Artificial general intelligence for radiation oncology

C Liu, Z Liu, J Holmes, L Zhang, L Zhang, Y Ding… - Meta-radiology, 2023 - Elsevier
The emergence of artificial general intelligence (AGI) is transforming radiation oncology. As
prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can …

[HTML][HTML] Magnetic resonance-based synthetic computed tomography images generated using generative adversarial networks for nasopharyngeal carcinoma …

Y Peng, S Chen, A Qin, M Chen, X Gao, Y Liu… - Radiotherapy and …, 2020 - Elsevier
Background and purpose To investigate the feasibility of synthesizing computed tomography
(CT) images from magnetic resonance (MR) images using generative adversarial networks …

Unsupervised pseudo CT generation using heterogenous multicentric CT/MR images and CycleGAN: Dosimetric assessment for 3D conformal radiotherapy

A Jabbarpour, SR Mahdavi, AV Sadr, G Esmaili… - Computers in biology …, 2022 - Elsevier
Purpose Absorbed dose calculation in magnetic resonance-guided radiation therapy
(MRgRT) is commonly based on pseudo CT (pCT) images. This study investigated the …