Artificial Intelligence Applied to Medical Imaging and Computational Biology

doi:10.3390/books978-3-0365-6488-3

Download Url(s)

https://mdpi.com/books/pdfview/book/6853

Contributor(s)

Rundo, Leonardo (editor)

Militello, Carmelo (editor)

Tangherloni, Andrea (editor)

Language

English

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Abstract

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.

URI

https://directory.doabooks.org/handle/20.500.12854/98811

Keywords

distribution patterns; fibroblast cells; HCT-8 colon-cancer cells; nature-inspired techniques; quantification; segmentation; myocardial infarction; vectorcardiogram; multivariate VMD; deep CNN; accuracy; deep learning; image segmentation; brain tumors; radiosurgery; magnetic resonance imaging; age-related macular degeneration; choroidal neovascularization; convolutional neural networks; image classification; optical coherence tomography angiography; brain metastasis; glioblastoma; machine learning; oxygenation; tumor infiltration; breast cancer detection; microwave breast imaging; computer-aided diagnosis (CAD); first-in-human (FiH) study; semantic segmentation; triceps surae muscle; medical image segmentation; breast cancer; pattern recognition; clinical feasibility; computer-assisted segmentation; artificial intelligence; orthopedics; neural network; mandible; craniomaxillofacial bone; multi-center; histopathology; lung cancer; supervised segmentation; unsupervised segmentation; stroke; fine tactile sensation; electroencephalography; evaluation; n/a