1. Artificial Intelligence in Radiation Therapy
- Author
-
Yabo Fu, Per-Ivar Lønne, Tian Liu, Hao Zhang, Xiaofeng Yang, Ibrahim Hadzic, Leonard Wee, Suraj Pai, Eric D. Morris, Carri K Glide-Hurst, Alberto Traverso, Chenyang Shen, RS: GROW - R2 - Basic and Translational Cancer Biology, Radiotherapie, and RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy
- 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 - 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.
- Published
- 2022