Next-Generation Medical Image Analysis: Multimodal, Decentralized, Fair and Reasoning-Centric Approaches

Dear Colleagues,

This Special Issue focuses on how emerging developments in artificial intelligence (AI), including multimodal learning; foundation models; agentic workflows; and explainable, decentralized, and reasoning-centric systems, are transforming the field of medical imaging. As modern healthcare increasingly relies on complex data sources such as radiology, pathology, and surgical scenarios, there is a growing need for AI models that can integrate diverse modalities, provide transparent and clinically meaningful reasoning, and operate reliably in real-world settings. We therefore invite researchers working across all aspects of medical imaging AI to submit original research articles and reviews for consideration.

This Special Issue will explore a broad range of topics, including multimodal representation learning; vision-language models; chain-of-thought and causal reasoning in clinical environments; and autonomous AI agents capable of performing data curation, report generation, decision support, and workflow optimization. We are also interested in studies addressing robustness, uncertainty, fairness, federated and privacy-preserving learning, and the challenges of scaling medical foundation models. Contributions may be theoretical, empirical, methodological, translational, or review-based, and we particularly welcome interdisciplinary and clinically grounded submissions.

This Special Issue will contribute to the expanding literature on AI for medical imaging and will deepen our understanding of how multimodal and agentic systems can support clinicians, enhance diagnostic accuracy, improve patient safety, and enable the development of trustworthy and explainable AI for use in healthcare. We aim to attract papers of interest to academics, clinicians, researchers, industry partners, and healthcare policymakers. We look forward to receiving your contributions.

Dr. Md Mostafa Kamal Sarker
Dr. Pramit Saha
Guest Editors

Manuscript Submission Information

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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. Big Data and Cognitive Computing 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.

• medical image analysis
• agentic AI
• multimodal learning
• vision-language models
• large language models
• large reasoning models
• clinical explainability and reasoning
• fairness
• reliable and trustworthy AI
• uncertainty
• interpretability
• human–AI collaboration
• federated learning