Potential of Deep Learning in Quantitative Magnetic Resonance Imaging for Personalized Radiotherapy.
Semin Radiat Oncol
; 32(4): 377-388, 2022 10.
Article
in En
| MEDLINE
| ID: mdl-36202440
Quantitative magnetic resonance imaging (qMRI) has been shown to provide many potential advantages for personalized adaptive radiotherapy (RT). Deep learning models have proven to increase efficiency, robustness and speed for different qMRI tasks. Therefore, this article discusses the current state-of-the-art and potential future opportunities as well as challenges related to the use of deep learning in qMRI for target contouring, quantitative parameter estimation and also the generation of synthetic computerized tomography (CT) data based on MRI in personalized RT.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Deep Learning
Limits:
Humans
Language:
En
Journal:
Semin Radiat Oncol
Journal subject:
NEOPLASIAS
/
RADIOLOGIA
Year:
2022
Document type:
Article
Affiliation country:
Netherlands
Country of publication:
United States