The Roles of Deep Learning in Cancer Radiotherapy
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Informatics and Big Data".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 2600
Special Issue Editor
Special Issue Information
Dear Colleagues,
The incorporation of deep learning into cancer radiotherapy signifies a groundbreaking evolution in oncology. By harnessing advanced algorithms and extensive datasets, deep learning models can significantly enhance the precision and efficiency of radiation treatments, including tumor detection, treatment target and critical organs delineation, treatment planning, quality assurance, and patient-outcome prediction. This Special Issue aims to delve into diverse applications of deep learning in radiotherapy, showcasing how these technologies can revolutionize cancer treatment. We welcome original research articles, reviews, and clinical studies that present innovative deep learning applications in radiotherapy, such as tumor detection, tumor and organ segmentation, treatment planning, dose prediction, and adaptive radiotherapy. We are particularly interested in contributions that illustrate the impact of deep learning on clinical workflows and patient outcomes. Potential topics include, but are not limited to, the following:
- Deep learning algorithms for tumor detection;
- Deep learning algorithms for tumor and organ segmentation;
- Artificial Intelligence driven automatic treatment planning;
- Predictive modeling of radiotherapy outcomes;
- Adaptive radiotherapy guided by deep learning;
- Integration of radiomics and deep learning in oncology;
- Deep learning algorithms for quality assurance procedures;
- Clinical validation of AI-driven radiotherapy tools;
- Challenges and solutions in implementing deep learning in clinical practice.
We eagerly anticipate your contributions that showcase the innovative applications of deep learning in advancing cancer radiotherapy.
Dr. Zhen Tian
Guest Editor
Manuscript Submission Information
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Keywords
- radiotherapy
- deep learning
- artificial Intelligence
- tumor detection
- image segmentation
- treatment planning
- outcome prediction
- radiomics
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