Artificial Intelligence and Computational Modeling for Next-Generation Medical Imaging and Therapy

Dear Colleagues,

Research at the intersection of AI and computational modeling is currently pivoting from passive diagnostics to active, predictive therapeutics. The key aims of the Special Issue include:

1. Multimodal Fusion and Radiomics: Developing deep learning architectures that integrate high-resolution imaging with genomic and longitudinal clinical data to identify "hidden" biomarkers for early-stage disease detection.
2. Predictive Digital Twins: Creating patient-specific computational models using multi-physics simulations to forecast tumor progression and personalize radiation dosages or drug delivery.
3. Generative AI for Reconstruction: Utilizing diffusion models and GANs to achieve super-resolution reconstruction, enabling ultra-low-dose scans without sacrificing diagnostic clarity.
4. Intelligent Interventions: Engineering autonomous surgical robotics and real-time guided radiotherapy systems that use computer vision for sub-millimeter motion compensation during procedures.
5. Automated Quality Assurance (QA): Developing AI-driven frameworks for real-time hardware calibration and treatment plan validation, ensuring consistency and safety while reducing human error.
6. Trustworthy and Ethical AI: Investigating explainable AI (XAI) and federated learning protocols to ensure clinical interpretability and data privacy across global, decentralized healthcare networks.

Dr. Nikolaos Dikaios
Guest Editor

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