Artificial Intelligence-generated Images in Radiation Oncology – Opportunities, Challenges, and Future Directions

A BSTRACT The era of computer science is advancing daily, and the most updated topic being discussed is artificial intelligence (AI). AI has dominated the technology due to its ability to work better, faster, smarter, and more effectively. One of the latest advancements in AI is its ability to convert the text to images. Using the textual prompts, the AI tools used the algorithm and pretrained models to generate the synthetic images that look such as real and high-resolution images. The generated images can be used in different fields for different purposes. In radiation oncology, AI-generated images can be a very helpful tool. The images generated by AI represent a promising frontier for transforming the landscape of cancer care. Advanced generative models, such as Generative Adversarial Networks and diffusion models, provide opportunities for clinical practice, education and training, simulation and treatment, and the execution of treatment. The AI-generated images can be used in radiation oncology for virtual patient modeling, generating synthetic images for dose calculation and virtual simulation, anatomical segmentation for training, and updating the machine learning algorithm. The article discusses the importance of AI-generated images and their potential use in radiation oncology and explores the challenges and future opportunities for improving cancer treatment through better integration of these images. The article also focuses on the ethical, regulatory, and practical challenges posed by the adoption of AI-generated visuals.