Advances in Medical Imaging: Techniques and Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".
Deadline for manuscript submissions: 20 November 2025 | Viewed by 227
Special Issue Editors
Interests: diagnostic radiology; computed tomography; magnetic resonance; diagnostic imaging artificial intelligence in medical imaging; digital health innovation; patient safety and quality in medical imaging; healthcare health literacy
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Medical imaging is fundamental to modern healthcare, supporting accurate diagnosis, therapeutic planning, and patient follow-up across a broad spectrum of diseases. Recent advances in imaging techniques, computational methods, and hardware development have significantly expanded the capabilities and applications of diagnostic imaging. This Special Issue aims to present cutting-edge research and innovative developments across various modalities, including computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, radiography, interventional radiology and hybrid imaging techniques. Particular attention will be given to novel acquisition methods, image reconstruction algorithms, quantitative imaging, and image-guided interventions. Furthermore, the integration of artificial intelligence, deep learning, and big data analytics into medical imaging workflows is transforming clinical practice and decision-making processes. Contributions that address patient safety, radiation dose optimization, and quality assurance in imaging are also welcome. The goal of this Special Issue is to bring together researchers, clinicians, and industry experts to share knowledge, foster collaboration, and highlight future directions in medical imaging science and technology.
Prof. Dr. Rui Pedro Pereira De Almeida
Dr. JungHwan Oh
Guest Editors
Manuscript Submission Information
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Keywords
- medical imaging
- diagnostic radiology
- computed tomography
- magnetic resonance imaging
- image reconstruction
- artificial intelligence
- quantitative imaging
- image-guided interventions
- radiation dose optimization
- image quality
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