Machine Learning Techniques for Medical Imaging, Sensing, and Analysis
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: closed (20 August 2022) | Viewed by 34652
Special Issue Editors
Interests: medical image analysis; computer vision; machine learning
Interests: multimodal brain image computing and analysis; machine learning; image segmentation
Special Issue Information
Dear Colleagues,
With the recent advancements in artificial intelligence, technologies for monitoring or diagnosing patients are also making great progress. However, there are still many unsolved challenges stemming from the lack of sufficient data, difficulty in labeling, and the heterogeneity of medical data. The goal of this Special Issue is to publish original manuscripts and the latest research regarding machine learning techniques that can be used for sensing or imaging bio-signals and predicting diagnosis or prognosis from medical images or signals. Towards this goal, we welcome submissions describing new cutting-edge machine learning and deep learning methods that address existing problems in the biomedical and health informatics fields.
Topics of interest include but are not limited to:
- Machine learning algorithms for medical image analysis;
- Disease classification and prognosis prediction;
- Segmentation and anomaly detection;
- Medical image generation and quality improvement;
- Medical image registration;
- Signal processing for predicting patient intentions or monitoring;
- Big or multi-modality data processing for predicting clinical outcomes.
Prof. Dr. Sang Hyun Park
Prof. Dr. Manhua Liu
Dr. Dong Hye Ye
Guest Editors
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