Machine Learning-Based Medical Image Analysis
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (1 August 2023) | Viewed by 30119
Special Issue Editors
Interests: deep-learning-based emotion recognition; medical image analysis; pattern recognition
Special Issues, Collections and Topics in MDPI journals
2. Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju 59626, Republic of Korea
Interests: magnetic resonance imaging; medical imaging; clinical application of machine learning and deep learning
Interests: object/image detection; segmentation; recognition; tracking; image understanding; action/behavior/gesture recognition; emotion recognition
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Machine learning and deep learning techniques have contributed to great success in medical image analysis. This Special Issue is being assembled to share various in-depth research results related to machine-learning and deep-learning-based medical image analysis methods, including, but not limited to, organ segmentation, detection of particular regions of interest, disease diagnosis and quantification, prediction of prognosis, and image restoration and synthesis. These applications may utilize various types of medical imaging modalities, such as X-ray, computerized tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), ultrasound, mammography, and pathological images.
It is our pleasure to invite you to join this Special Issue, entitled “Machine Learning-Based Medical Image Analysis”, whereby you are welcome to contribute a manuscript on your valuable research progress. Thank you very much.
Prof. Soo-Hyung Kim
Prof. Ilwoo Park
Prof. In Seop Na
Guest Editors
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Keywords
- machine learning and deep learning
- medical image analysis
- X-ray, CT, MRI, PET, ultrasound, mammography, and pathological images
- lesion segmentation, detection, quantification and diagnosis
- computer-aided medical imaging tool
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