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- Guangming Zhu, Bin Jiang, Liz Tong, Yuan Xie, Greg Zaharchuk, and Max Wintermark.
- Neuroradiology Section, Department of Radiology, Stanford Healthcare, Stanford, CA, United States.
- Front Neurol. 2019 Jan 1; 10: 869.
AbstractMany clinical applications based on deep learning and pertaining to radiology have been proposed and studied in radiology for classification, risk assessment, segmentation tasks, diagnosis, prognosis, and even prediction of therapy responses. There are many other innovative applications of AI in various technical aspects of medical imaging, particularly applied to the acquisition of images, ranging from removing image artifacts, normalizing/harmonizing images, improving image quality, lowering radiation and contrast dose, and shortening the duration of imaging studies. This article will address this topic and will seek to present an overview of deep learning applied to neuroimaging techniques.
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