BDAMI 2025
2nd IEEE Workshop on Big Data Analytics for Medical Imaging
In conjunction with IEEE Big Data 2025 Macau SAR, China
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Recent advances in medical imaging have led to an explosive growth in diagnostic data from sources such as computed tomography (CT), magnetic resonance imaging (MRI), radiography, ultrasound, and digital pathology. The primary challenge has shifted from image acquisition to the intelligent interpretation, integration, and management of these data for clinical decision-making. Big Data analytics—enhanced by recent breakthroughs in machine learning (ML), deep learning (DL), and generative AI—is emerging as a transformative approach to unlock clinically meaningful insights from complex imaging datasets.
We propose the second edition of the workshop, reflecting our sustained commitment to advancing research at the intersection of Big Data and Medical Imaging, and our intent to support the growth of this interdisciplinary community over time.
This workshop aims to foster collaboration between the Big Data and Medical Imaging communities, focusing on novel methods, frameworks, and datasets that support improved diagnosis, patient treatment personalization, clinical workflow optimization, and the detection of misinformation in medical imaging. We welcome innovative and interdisciplinary research that bridges computational techniques and clinical applications, with particular attention to real-time analytics, edge computing, data privacy, and fairness in AI-driven medical imaging.
TOPICS
TOPICS
BDAMI is aimed at different categories of professionals interested in harnessing the potential of Big Data in medical imaging.
Medical process support
Medical process support
Big Data Analytics for predictive diagnostics using multimodal imaging
Personalized treatment planning via AI-driven imaging pipelines
Workflow optimization in hospitals through imaging-based analytics
Data Analytics for disease progression
Large Language Models (LLMs) for radiology report generation and image annotation
Large Language Models (LLMs) for radiology report generation and image annotation
Monitoring disease progression via longitudinal image analysis
Integration of electronic health records (EHR) and imaging data for holistic analysis
Medical Image security
Medical Image security
Detection of deepfakes 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
Medical Image Processing
Medical Image Processing
Big Data Analytics for anomalies detection on medical imaging
Big Data Analytics for medical images enhancement and reconstruction
Big Data Analytics for noise reduction in medical images
Explainable AI (XAI) and model interpretability in clinical imaging tasks
Real-time medical image processing on edge and mobile devices
Anomaly and rare disease detection using big imaging datasets
Benchmarking and evaluation methodologies for AI in medical imaging
Medical Image Dataset
Medical Image Dataset
Curated datasets for big data analytics in medical imaging
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
IMPORTANT DATES
IMPORTANT DATES
October 1, 2025: Due date for full workshop papers submission
Nov 10, 2025: Notification of paper acceptance to authors
Nov 23, 2025: Camera-ready of accepted papers (strict)
Dec 8-11, 2025: Workshop (Full Online)
SUBMISSION AND REGISTRATION
SUBMISSION AND REGISTRATION
Authors are invited to submit papers up to 10 pages references included (6 to 8 pages are recommended) in the IEEE 2-column format (IEEE Computer Society Proceedings Manuscript template) that can be found here.
All papers must be submitted via the conference submission system for the workshop.
Full registration for IEEE BigData 2025 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
ORGANIZERS
Carmen Bisogni
Carmen Bisogni
University of Salerno, Salerno, Italy
Shaohua Wan
Shaohua Wan
University of Electronic Science and Technology of China, Shenzhen, China
Marco Salvatore Zappatore
Marco Salvatore Zappatore
University of Salento, Lecce, Italy
Lucia Cimmino
Lucia Cimmino
University of Salerno, Salerno, Italy
Program Committee (Tentative)
Program Committee (Tentative)
Matteo Polsinelli, University of Salerno, Italy
Chiara Pero, University of Salerno, Italy
Imad Rida, Université de Technologie de Compiègne, France
Giorgio De Nunzio, University of Salento, Italy
Valerio De Luca, Pegaso telematic university, Italy
Saiyed Umer, Aliah University, India
Fabio Narducci, University of Salerno, Italy
Lucia Cascone, University of Salerno, Italy
Andrea Loddo, University of Cagliari, Italy
CONTACTS
CONTACTS
For any information, please contact
Carmen Bisogni
University of Salerno
Salerno, Italy
cbisogni@unisa.it
SPECIAL ISSUE ON MULTIMEDIA TOOLS AND APPLICATIONS
SPECIAL ISSUE ON MULTIMEDIA TOOLS AND APPLICATIONS
"Explainable AI (XAI) for Biometric Authentication and Medical Imaging: A Cross-Disciplinary Challenge"
The authors of chosen papers presented at BDAMI25 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.
SPECIAL ISSUE ON IMAGE AND VISION COMPUTING
SPECIAL ISSUE ON IMAGE AND VISION COMPUTING
"Security-AI: Attacks on AI Systems in Computer Vision "
The authors of chosen papers presented at BDAMI25 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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