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Artificial Intelligence in Radiation Therapy
- Source :
- IEEE Trans Radiat Plasma Med Sci, IEEE Transactions on Radiation and Plasma Medical Sciences, 6(2), 158-181. IEEE
- Publication Year :
- 2022
- Publisher :
- IEEE, 2022.
-
Abstract
- Artificial intelligence (AI) has great potential to transform the clinical workflow of radiotherapy. Since the introduction of deep neural networks (DNNs), many AI-based methods have been proposed to address challenges in different aspects of radiotherapy. Commercial vendors have started to release AI-based tools that can be readily integrated to the established clinical workflow. To show the recent progress in AI-aided radiotherapy, we have reviewed AI-based studies in five major aspects of radiotherapy, including image reconstruction, image registration, image segmentation, image synthesis, and automatic treatment planning. In each section, we summarized and categorized the recently published methods, followed by a discussion of the challenges, concerns, and future development. Given the rapid development of AI-aided radiotherapy, the efficiency and effectiveness of radiotherapy in the future could be substantially improved through intelligent automation of various aspects of radiotherapy.
- Subjects :
- BEAM COMPUTED-TOMOGRAPHY
treatment planning
Computer science
medicine.medical_treatment
Image registration
Artificial intelligence (AI)
PLAN QUALITY
Article
MODULATED ARC THERAPY
DEFORMABLE IMAGE REGISTRATION
KNOWLEDGE-BASED PREDICTION
HEAD-AND-NECK
medicine
Radiology, Nuclear Medicine and imaging
AUTOMATIC SEGMENTATION
Radiation treatment planning
Instrumentation
image segmentation
radiotherapy
ANATOMIC CHANGES
NEURAL-NETWORK
business.industry
MULTICRITERIA OPTIMIZATION
Image segmentation
image reconstruction
Automation
Atomic and Molecular Physics, and Optics
Image synthesis
Radiation therapy
image registration
ComputingMethodologies_PATTERNRECOGNITION
Workflow
Deep neural networks
Artificial intelligence
business
image synthesis
Subjects
Details
- Language :
- English
- ISSN :
- 24697303 and 24697311
- Volume :
- 6
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Radiation and Plasma Medical Sciences
- Accession number :
- edsair.doi.dedup.....6edf2198be56554aa92f24dd84164942