Radiological images and machine learning: Trends, perspectives, and prospects

The application of machine learning to radiological images is an increasingly active research area that is expected to grow in the next five to ten years. Recent advances in machine learning have the potential to recognize and classify complex patterns from different radiological imaging modalities...

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Veröffentlicht in:	Computers in biology and medicine Jg. 108; S. 354 - 370
Hauptverfasser:	Zhang, Zhenwei, Sejdić, Ervin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Ltd 01.05.2019 Elsevier Limited
Schlagworte:	Accuracy Algorithms Alzheimer's disease Artificial intelligence Brain Cancer Clinical decision making Cognitive ability Computed tomography Decision making Deep Learning Deep neural network Fractures Gamma rays Human performance Humans Image management Image processing Image Processing, Computer-Assisted Image registration Image retrieval Image segmentation Imaging modalities Keywords Learning algorithms Machine learning Magnetic Resonance Imaging Mammography Medical imaging Medical research Models, Theoretical Neural networks Neuroimaging Neurological diseases NMR Nuclear magnetic resonance Positron emission Positron emission tomography Principal components analysis Radiology Ultrasonic imaging X-rays Deep learning Deep neural network Imaging modalities Machine learning
ISSN:	0010-4825, 1879-0534, 1879-0534
Online-Zugang:	Volltext
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