Information Fusion in Medical Image Computing
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Deadline for manuscript submissions: closed (15 August 2021) | Viewed by 3159
Special Issue Editor
Interests: multimodal systems; sensor fusion; big data analytics; Internet of Things; computer vision; pattern recognition; data mining; medical image computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The acquisition of biomedical data happens in a broad range of formats and a wide range of application settings and can range from unstructured text notes to structured data records and biomedical sensor signals, either as 1D signals, 2D images or 3D volumes, or even higher dimensional data such as temporal 3D sequences. This massive amount of heterogenous data needs to be processed in an appropriate way so that useful information and knowledge can be extracted and used to provide automatic, computer-based decision support systems.
In this Special Issue, contributions are solicited from researchers and practitioners on recent advances in algorithms and applications that involve fusing or combining medical information from multiple sources, and intelligent processing of this information based on innovative machine learning, deep learning and AI approaches, and their implementations in different biomedical computing application settings.
Topics for this Special Issue include (but are not limited to):
- Information fusion of structured and unstructured data for biomedical systems;
- Machine learning and deep learning for biomedical image data;
- Multisensor, multimodal, and multiview learning;
- Combining multiple sources and models for biomedical data;
- Early, feature and late fusion for biomedical data;
- Hierarchical models and architectures for biomedical fusion systems;
- Joint feature learning and cross modal learning.
Dr. Girija Chetty
Guest Editor
Manuscript Submission Information
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Keywords
- Information fusion
- Multimodal
- Biomedical
- Machine learning
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