Machine learning applications in medical image analysis
- Submission status
- Closed
- Submission deadline
Significant breakthroughs in the capabilities of machine learning (ML) algorithms in recent years coupled with advancements in imaging tools have precipitated a revolution in automated medical image analysis. ML-based methods are increasingly being used to extract data from diverse imaging modalities and guide clinical decision making in a range of specialties including radiology, ophthalmology, neurology, respiratory medicine and cancer.
This Collection aims to bring together original research on all aspects of ML-based medical image analysis, including but not limited to technological developments and new clinical applications.
Editors
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Syed Ahmad Chan Bukhari
St. John’s University, USA
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Simon Duchesne
Université Laval, Canada
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Huazhu Fu
Agency for Science, Technology and Research, Singapore
