Call for papers
AI in Particle Therapy
Articles will address most pressing issues in PT AI, resulting in a high-ranking, impactful issue
Guest editors:
Dr. Lennart Volz, Deputy Group Leader Medical Physics Group, GSI Helmholtz Centre for Heavy Ion Research
Dr. Hao Peng, Professor of UT Southwestern Medical Group.
Special issue information:
The value of artificial intelligence in particle therapy has rapidly evolved over the last five years. The goals of the IJPT special issue are to expand our knowledge of the overall benefits and challenges related to the use of AI in particle therapy, to provide greater clarity on AI-related treatment planning and quality assurance methodologies, and to determine whether data on the use of AI aids us in our pursuit of clinical workflow efficiency, patient referral, and outcome prediction.
Potential topics for this issue:
- Treatment planning
- Parameter selection, streamlining plan generation
- Dose prediction
- Single-pencil beam, single-field or total dose, consideration of LET and RBE3.
- Imaging
- Image synthesis, stopping power prediction
- Clinical workflow efficiency
- Treatment verification and quality assurance
- Verifying AI dose engines, automated plan QA, issue detection/prediction, online range/dose verification
- Adaptation
- Predicting anatomical changes, augmented re-planning, motion mitigation
- Patient referral and outcome prediction
- NTCP/TCP prediction, prediction/understanding of adverse effects
Manuscript submission information:
Please follow the Guide for Author and submit via Editorial Manager. And please choose "VSI: AI in Particle Therapy" at the Article Type stage.
This special issue will offer a 30% APC waiver for authors.
Why publish in this Special Issue?
- Special Issue articles are published together on ScienceDirect, making it incredibly easy for other researchers to discover your work.
- Special content articles are downloaded on ScienceDirect twice as often within the first 24 months than articles published in regular issues.
- Special content articles attract 20% more citations in the first 24 months than articles published in regular issues.
- All articles in this special issue will be reviewed by no fewer than two independent experts to ensure the quality, originality and novelty of the work published.
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