Emerging Trends in Artificial Intelligence for Biomedical Image Analysis
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 20 May 2025 | Viewed by 22
Special Issue Editor
Interests: computer vision; image analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) has transformed biomedical image analysis, providing innovative solutions for disease diagnosis, treatment planning, and patient monitoring.
This Special Issue highlights the latest trends in AI-driven methodologies, such as deep learning, reinforcement learning, and hybrid approaches, which are tailored to the unique challenges of biomedical imaging and integrated with the Internet of Things (IoT) and advanced sensor technologies. IoT-enabled devices, along with real-time sensors, contribute vast streams of multi-modal data that AI systems can analyze to enhance precision in medical imaging applications. Noteworthy advancements in image segmentation, classification, and anomaly detection show how these technologies, combined with continuous sensor data, elevate precision and efficiency in diagnostics and remote patient monitoring.
Additionally, integrating explainable AI into clinical workflows is vital for interpreting complex model predictions, fostering trust and broader adoption in healthcare. This Special Issue also explores domain-specific applications, such as AI for radiology, pathology, and retinal image analysis, emphasizing the role of IoT and sensor fusion in enhancing diagnostic accuracy. Despite these advancements, challenges such as data privacy, model generalizability, and regulatory hurdles persist, particularly with IoT data security.
Moreover, this Special Issue will discuss how to integrate data from different imaging techniques (such as MRI, CT, PET, and ultrasound) to provide more comprehensive diagnostic information; to study the potential of multi-modal data fusion in improving the accuracy of disease detection and classification; and the application of AR and VR technologies in biomedical image analysis, particularly in surgical planning and educational training.
This Special Issue addresses these barriers by presenting novel frameworks, benchmarking studies, and emerging standards for ethical, IoT-integrated AI in healthcare. By featuring state-of-the-art research and comprehensive reviews, this Special Issue provides a roadmap for future research and development in AI and IoT-enabled biomedical image analysis, poised to revolutionize the field and ultimately improve patient outcomes.
Prof. Dr. Francesco Mercaldo
Guest Editor
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Keywords
- computer vision
- medical image analysis
- deep learning
- artificial intelligence
- healthcare
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