--------------------- Workshop information ---------------------


Call for Papers - 2nd IEEE Workshop on Big Data Analytics for Medical Imaging

In conjunction with IEEE Big Data 2025 (https://conferences.cis.um.edu.mo/ieeebigdata2025/)

FULL ONLINE

EXTENDED SUBMISSION DEADLINE: October 30, 2025



About The Workshop
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Medical imaging technology has resulted in an unprecedented volume of diagnostic data from a variety of sources, including computed tomography (CT), magnetic resonance imaging (MRI), radiography, and more. However, the key problem is no longer just capturing high-resolution pictures, but also effectively understanding and extracting information from this vast amount of data. This is where Big Data analytics come in.
Big Data analytics in medical imaging seeks to extract important information, detect patterns and trends, and assist critical clinical choices. This approach, further helped by machine learning and deep learning techniques not only promises to improve diagnostic and treatment accuracy, but also to increase operational efficiency in healthcare services.
This workshop aims to attract the interest of Big Data and Medical Imaging researchers in developing novel methodologies, datasets, and approaches for diagnosis, patient treatment, medical image management optimization, and misinformation and disinformation detection.


Topics
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The topics of interest are inspired from the themes above and include, but are not limited to:
Medical process support:
Big Data Analytics for predictive diagnostics with medical imaging
Big Data Analytics for personalised treatment with medical imaging
Big Data Analytics for medical imaging supporting hospital workflow optimisation
Data Analytics for disease progression
Medical Image security:
Deepfakes detection on Medical Imaging
Misinformation and disinformation on medical imaging
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
Medical Image Dataset:
Curated datasets for big data analytics in medical imaging
Synthetic datasets for big data analytics in medical imaging

Submission Information
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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).
All papers must be submitted via the conference submission system for the workshop. Full registration of IEEE BigData 2025 is required for at least one of the authors for participating in the workshop.

--------------------- Special Issues Opportunity!!! ---------------------

The authors of chosen papers presented at BDAMI25 have the opportunity to submit an extended version of their contributions to one of the following two special issues, ensuring that the submitted version aligns with the scope and objectives of the selected venue:


"Explainable AI (XAI) for Biometric Authentication and Medical Imaging: A Cross-Disciplinary Challenge" on Multimedia Tools and Applications (MTAP) Springer.
"Security-AI: Attacks on AI Systems in Computer Vision " on Image and Vision Computing (IMAVIS) Elsevier.
The links to both special issue calls for papers are available on the workshop website.
The deadline for the Special Issues will allow the authors of BDAMI25 time to incorporate the feedback from reviewers and conference participants into the extended version to be submitted to the SIs.


Workshop Co-Chairs
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Carmen Bisogni, University of Salerno (Italy), cbisogni@unisa.it
Shaohua Wan, UESTC (China), shaohua.wan@uestc.edu.cn
Marco Zappatore, University of Salento (Italy), marcosalvatore.zappatore@unisalento.it
Lucia Cimmino, University of Salerno (Italy), lcimmino@unisa.it