Recent Advance of Machine Learning in Biomedical Image Analysis: 2nd Edition
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: closed (20 February 2025) | Viewed by 576
Special Issue Editors
Interests: computer vision; medical image analysis
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning; medical image analysis; computer vision
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, the field of biomedical image analysis has gained significant importance due to the growing availability of medical imaging data and the need for accurate and efficient analysis. Machine learning (ML) techniques have emerged as a promising solution to address these challenges, with wide use in various applications, such as computer-aided diagnosis, medical image segmentation, registration, retrieval, classification, etc. The leading conferences and journals of the medical image analysis community, such as MICCAI and IEEE TMI, have recently published several advanced influential research articles using advanced ML techniques, such as transformer and auto ML. With an increase in data volume, advanced ML techniques are becoming increasingly important in biomedical image analysis.
The second edition of this Special Issue aims to present the latest research developments in machine learning applied to biomedical image analysis. The topics of interest include, but are not limited to, the following:
- Semantic segmentation of medical images;
- Computer-aided detection and diagnosis;
- Learning from weak or noisy annotations;
- Transfer learning and domain adaptation;
- Uncertainty estimation for medical diagnosis;
- Unsupervised deep learning and representation learning;
- Transformer-based medical image analysis method;
- Deep learning applications in radiology, pathology, endoscopy, dermatology, ophthalmology and beyond.
Dr. Zhiming Luo
Dr. Sheng Lian
Guest Editors
Manuscript Submission Information
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Keywords
- machine learning
- deep learning
- artificial intelligence
- unsupervised feature learning
- medical imaging analysis
- computer-aided diagnosis
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