BDAMI 2026

3rd Workshop on Big Data Analytics for Medical Imaging

In conjunction with IEEE Big Data 2026

Phoenix, Arizona, USA

TOPICS

IMPORTANT DATES

SUBMISSION AND REGISTRATION

ORGANIZERS

CONTACTS

SPECIAL ISSUE ON MULTIMEDIA (MDPI)

The growing adoption of synthetic medical images generated through artificial intelligence is rapidly reshaping the role of Big Data in medical imaging and healthcare applications. Advances in generative AI, machine learning, and deep learning now allow the creation of highly realistic medical images that simulate clinical data across modalities such as CT, MRI, radiography, ultrasound, and digital pathology. From a Big Data perspective, synthetic imaging is becoming a crucial solution to challenges such as data scarcity, class imbalance, limited annotations, and privacy constraints.

At the same time, the continuous growth in the volume and complexity of medical imaging data requires advanced computational methods for efficient processing, integration, and interpretation of large-scale imaging repositories. In this context, Big Data analytics combined with AI technologies is playing a key role in transforming medical imaging data into actionable clinical knowledge.

With this third edition, the workshop aims to strengthen collaboration between the Big Data and Medical Imaging communities and promote interdisciplinary research on AI-enabled and data-centric solutions for healthcare applications.
The workshop welcomes contributions on topics including synthetic and generative medical imaging, large-scale image analytics, intelligent diagnostic systems, personalized medicine, clinical workflow optimization, misinformation detection in medical imaging, real-time analytics, edge computing, trustworthy AI, and privacy-preserving data management.

TOPICS

BDAMI is aimed at different categories of professionals interested in harnessing the potential of Big Data in medical imaging.

Clinical Intelligence and Decision Support

Big Data Analytics for predictive diagnostics using multimodal imaging
Personalized treatment planning via AI-driven imaging pipelines
Anomaly and rare disease detection using big imaging datasets
Monitoring disease progression via longitudinal image analysis
Integration of electronic health records (EHR) and imaging data for holistic analysis
Retrieval-Augmented Generation (RAG) frameworks for multimodal medical imaging interpretation and clinical decision support
Autonomous AI agents for adaptive image analysis, monitoring, and clinical recommendation generation

Advanced Medical Image Computing and Generation

Generative AI (e.g., GANs, diffusion models) for image synthesis and data augmentation
Advanced reconstruction techniques from low-dose or undersampled imaging
Image denoising, super-resolution, and enhancement through deep learning
Real-time medical image processing on edge and mobile devices
Large Language Models (LLMs) for radiology report generation and image annotation

Trustworthy, Explainable, and Privacy-Preserving AI

Detection of deep fakes and synthetic media in medical imaging
Misinformation and disinformation detection in radiological reports and image metadata
Federated learning and privacy-preserving analysis of distributed imaging datasets
Explainable AI (XAI) and model interpretability in clinical imaging tasks
Benchmarking and evaluation methodologies for AI in medical imaging

Autonomous Healthcare Systems and Workflow Optimization

Workflow optimization in hospitals through imaging-based analytics
Agentic AI systems for autonomous clinical workflow orchestration and radiology assistance

IMPORTANT DATES

October 1, 2026: Due date for full workshop papers submission

Nov 07, 2026: Notification of paper acceptance to authors

Nov 14, 2026: Camera-ready of accepted papers (strict)

Dec 14-17, 2026: Conference Dates (Full Online Workshop)

SUBMISSION AND REGISTRATION

Please submit a full-length paper (up to 10 page IEEE 2-column format, reference pages counted in the 10 pages) through the online submission system.

Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines.

Full registration for IEEE BigData 2026 is required for at least one of the authors to participate in the workshop and have the paper published in the proceedings.

Registration details and fees are available at the main conference website.

ORGANIZERS

Carmen Bisogni

University of Salerno, Salerno, Italy

Shaohua Wan

University of Electronic Science and Technology of China, Shenzhen, China

Marco Salvatore Zappatore

University of Salento, Lecce, Italy

Lucia Cimmino

University of Salerno, Salerno, Italy

Program Committee (Tentative)

Sajid Anwar, Institute of Management Science, Pakistan
Umberto Bilotti, University of Salerno, Italy
Christopher Buratti, Università Politecnica delle Marche, Italy
Shovanlal Gayen, Jadavpur University, India
Francesca Miccoli, University of Salento, Italy
Prabhat Kumar, Banaras Hindu University, India
Maddalena Migliaccio, University of Salerno, Italy
Luigi Emanuele Sica, University of Salerno, Italy
Benedetto Simone, University of Salerno, Italy

CONTACTS

For any information, please contact

Carmen Bisogni
University of Salerno
Salerno, Italy
cbisogni@unisa.it

SPECIAL ISSUE ON MULTIMEDIA (MDPI)

"Intelligent Multimedia Systems for E-Health, Biosignal Processing, and Bioengineering "

The authors of papers presented at BDAMI26 have the opportunity to submit an extended version of their contributions that incorporates both the reviewers' comments on their conference paper and the feedback obtained during the conference presentation. It is important to note that the extended version is expected to contain a significant scientific contribution, such as new algorithms, experiments, or qualitative/quantitative comparisons, and to not transfer large sections of the conference paper.

The call for paper is here.

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