Call for Papers
We invite the submission of original research papers to the 6th International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2025). The conference welcomes contributions that explore the intersection of medical imaging, computer-aided diagnosis, and cutting-edge AI technologies, including transformers, LLMs, generative models, and deep learning.
MICAD 2025 is organized into six main tracks with a Track 7 with open topics related to any aspect of the conference as below.
Submission to the conference will undergo rigorous single blind peer review process and those accepted and presented ones will be published in the MICAD 2025 Conference Proceedings, in the Springer flagship series Lecture Notes in Electrical Engineering with planned inclusion in EI-Compendex, Scopus, and other major indexing services.
Important Dates
Full Paper Due: Aug. 19, 2025
(AoE)
Notification Date: Sept. 17, 2025
Registration Deadline: Oct. 10, 2025
Conference Date: Nov. 19-21, 2025
The List Of Topics
| T1. AI-Powered Medical Imaging | T2. Imaging Modalities and Computational Techniques |
|---|---|
| Deep learning in medical imaging | Magnetic Resonance Imaging (MRI) |
| Transformer-based image analysis | Computed Tomography (CT) |
| Generative AI for image enhancement and synthesis | Positron Emission Tomography (PET) |
| Self-supervised and foundation models for medical tasks | Optical and Photoacoustic Imaging |
| Multimodal and cross-domain learning | Ultrasonography and high-resolution imaging |
| Federated and privacy-preserving learning in imaging | Image reconstruction and acquisition |
| Explainable AI in clinical imaging applications | Image registration and fusion |
| Integration of LLMs for radiology reporting and workflow automation | Molecular, pathology, and interventional imaging |
| Neuroimaging and cardiac imaging | |
| Imaging-genomics integration | |
| T3. Image Processing, Analysis & Visualization | T4. Computer-Aided Diagnosis and Decision Support |
| Medical image segmentation and classification | AI-driven decision support systems |
| Feature extraction and pattern recognition | Radiomics and quantitative imaging biomarkers |
| Statistical, mathematical, and physics-based models | CAD systems and workstation design |
| Image-based computational anatomy and physiology | Human–AI collaboration and interaction |
| Data visualization and visual analytics | Performance evaluation and benchmarking of AI models |
| Shape modeling and representation | Diagnostic LLMs and prompt-based medical reasoning |
| Image-guided surgery and interventions | AR/VR applications for diagnostics and training |
| Surgical tracking and navigation systems | Clinical deployment and evaluation of AI tools |
| T5. Robotics, Devices & Smart Systems in Healthcare | T6. Photonics and Emerging Biomedical Imaging Technologies |
| Medical robotics and surgical haptics | Laser-based diagnostic tools |
| Image-guided robotic interventions- RFID and IoT solutions for healthcare | Biophotonics and optical coherence tomography |
| RFID and IoT solutions for healthcare | Novel sensors and imaging devices |
| Wearable and smart sensing technologies | Photon transport modeling in tissue |
| Real-time data processing in clinical settings | Photonic data integration with AI models |
| Cloud and edge computing for medical imaging | Spectroscopic imaging and applications in pathology |
| Cybersecurity and data governance in AI-driven systems | Hybrid imaging technologies |
| T7:Other related topics |