AI-Driven Medical Image/Video Processing
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 53
Special Issue Editor
Interests: deep learning algorithm; image/video signal processing; medical image processing and system; image/video communication and systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) has emerged as a transformative force in the field of medical image and video processing, offering unprecedented opportunities to improve diagnosis, treatment planning, and patient outcomes. As AI-driven image processing continues to shape modern technology, addressing challenges, such as those of computational efficiency, interpretability, and ethical considerations, remains crucial. Additionally, there is a need to foster interdisciplinary collaboration and knowledge exchange between clinical professionals and AI experts, bringing more accurate diagnosis and treatment through an integrated approach to the disease. This special issue aims to explore the latest theoretical advancements, methodologies, and practical applications of AI in medical imaging and video analysis. We invite contributions that highlight innovative uses of AI-driven techniques to address challenges in medical image interpretation, video analysis, multimodal imaging, and clinical decision support. Through this issue, we seek to foster a deeper understanding of AI's role in revolutionizing healthcare and its potential to enhance the precision, efficiency, and accessibility of medical practices worldwide.
Prof. Dr. Jitae Shin
Guest Editor
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Keywords
- AI techniques in medical imaging
- medical image/video processing
- multimodal imaging
- diagnostic imaging
- data augmentation and synthetic data
- explainable AI in clinical decision support
- deep learning for image/video analysis
- medical image and video enhancement
- applications of large language models (LLMs) in medical domain
- AI-driven smart devices for medical image/video
- clinical decision support
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