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Artificial Intelligence Applied to Medical Imaging and Computational Biology
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Medical imaging and computational biology continuously pose new fundamental medical and biological questions that often give rise to novel challenges in Artificial Intelligence. These research fields present an increasing need for the application of cutting-edge computational approaches that generally involve machine learning or computational intelligence techniques, which can effectively perform bioimage and biosignal processing in different clinical areas.
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Keywords
- accuracy
- age-related macular degeneration
- artificial intelligence
- brain metastasis
- brain tumors
- Breast cancer
- breast cancer detection
- choroidal neovascularization
- clinical feasibility
- computer-aided diagnosis (CAD)
- computer-assisted segmentation
- convolutional neural networks
- craniomaxillofacial bone
- deep CNN
- deep learning
- distribution patterns
- Electroencephalography
- Evaluation
- fibroblast cells
- fine tactile sensation
- first-in-human (FiH) study
- Glioblastoma
- HCT-8 colon-cancer cells
- histopathology
- Humanities
- image classification
- image segmentation
- lung cancer
- Machine learning
- Magnetic Resonance Imaging
- Mandible
- medical image segmentation
- microwave breast imaging
- multi-center
- multivariate VMD
- Myocardial Infarction
- n/a
- nature-inspired techniques
- Neural Network
- optical coherence tomography angiography
- Orthopedics
- oxygenation
- pattern recognition
- quantification
- radiosurgery
- segmentation
- semantic segmentation
- Social interaction
- Social issues & processes
- Society & culture: general
- Society & Social Sciences
- Stroke
- supervised segmentation
- triceps surae muscle
- tumor infiltration
- unsupervised segmentation
- vectorcardiogram
Links
DOI: 10.3390/books978-3-0365-6488-3Editions