Artificial Intelligence in Medical Imaging: Progress, Challenges and Perspectives
A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "Medical Imaging".
Deadline for manuscript submissions: 31 March 2027 | Viewed by 67
Special Issue Editor
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) becomes a transformative force in medical imaging, driving significant advances across a wide range of modalities, including magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), ultrasound, and X-ray imaging. It enables breakthroughs in image acquisition, reconstruction, analysis, and clinical decision support. However, the field is currently transitioning from task-specific models toward more generalizable, reliable, and clinically deployable paradigms. Emerging trends, such as multimodal learning, foundation models, physics-informed AI, uncertainty-aware modeling, generative AI, and agentic AI systems, are redefining how imaging data are acquired, reconstructed, interpreted, and integrated with broader clinical information.
This Special Issue aims to provide a comprehensive and forward-looking perspective on Artificial Intelligence in Medical Imaging, with a particular focus on bridging methodological innovation, theoretical foundations, and real-world clinical translation. It seeks to highlight recent progress while critically examining key challenges, including data heterogeneity across institutions and populations, robustness under distribution shifts, AI interpretability, and the integration of domain knowledge into learning frameworks, and theoretical analysis of generalization and uncertainty in medical AI systems.
We welcome original research articles and reviews that advance both theoretical understanding and practical deployment. Topics of interest include, but are not limited to:
- Multimodal and multi-source learning
- Foundation models and large-scale pretraining for medical imaging
- Agentic AI in medical imaging workflows
- Physics-informed and model-based deep learning for image computing
- Theoretical analysis of generalization, robustness, and uncertainty
- Data-efficient AI in source-restricted environments
- Cross-domain generalization and federated learning
- Clinical translation, validation, and real-world deployment
- Benchmarking, datasets, and reproducibility in medical AI
- Emerging paradigms and future perspectives in AI-driven imaging
By bringing together advances across methodology, theory, and clinical practice, this Special Issue aims to foster a deeper understanding of the next-generation AI systems that are not only accurate but also robust, explainable, and clinically impactful, ultimately shaping the future of medical imaging.
Dr. Zi Wang
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence
- medical imaging
- multimodal learning
- foundation models
- generative AI
- agentic AI
- physics-informed learning
- robustness and reliability
- clinical translation
- computational imaging
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