Artificial Intelligence in Magnetic Resonance Imaging(MRI)
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Machine Learning and Artificial Intelligence in Diagnostics".
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 210
Special Issue Editor
2. Visiting Senior Researcher, Department of Neuroimaging, IOPPN King’s College, London, UK
Interests: medical physics; radiology; nuclear medicine; artificial intelligence in biomedical imaging and radiotherapy
Special Issue Information
Dear Colleagues,
Artificial Intelligence (AI) and Machine Learning (ML) applications in all scientific fields have produced an extraordinary explosion of advanced data analysis tools. Due to the intrinsic nature of medical imaging data, AI is intensively employed in this field in recent years, and it is becoming increasingly prevalent especially in Magnetic Resonance Imaging (MRI) since the large quantitative nature of MRI data can be efficiently reconstructed and transformed into mineable qualitative clinical information using AI.
These ML approaches can be utilized for registration, segmentation, and classification of medical images aiding in detection and prediction, in image optimization with faster imaging procedures with augmented workflows and reduction of artifacts, as well as in the combination of genomics and radiogenomics pushing the boundaries of conventional imaging thus revolutionizing MRI.
Nevertheless, the large body of literature constantly being published, stresses the lack of standardization, and suffers from reproducibility testing, as well as a robust methodological approach to multicenter reproducible results.
As a consequence, the goal of this special issue is to address the above-previously mentioned opportunities and challenges and to present a comprehensive overview of the latest AI advances, compiling an update of the state-of-the-art efforts in MR Imaging acquisition, processing, and clinical applications.
Dr. Ioannis M. Tsougos
Guest Editor
Manuscript Submission Information
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Keywords
- artificial intelligence
- machine learning
- magnetic resonance imaging (MRI)
