Neuroimaging clinics of North America
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Neuroimaging Clin. N. Am. · Nov 2020
ReviewAn East Coast Perspective on Artificial Intelligence and Machine Learning: Part 2: Ischemic Stroke Imaging and Triage.
Acute ischemic stroke constitutes approximately 85% of strokes. Most strokes occur in community settings; thus, automatic algorithms techniques are attractive for managing these cases. ⋯ This article reviews algorithms for artificial intelligence techniques that may be used to detect and localize acute ischemic stroke. We describe artificial intelligence algorithms for these tasks and illustrate them with examples.
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This article reviews the history of artificial intelligence and introduces the reader to major events that prompted interest in the field, as well as pitfalls and challenges that have slowed its development. The purpose of this article is to provide a high-level historical perspective on the development of the field over the past decades, highlighting the potential of the field for transforming health care, but also the importance of setting realistic expectations for artificial intelligence applications to avoid repeating historical cyclical trends and a third "artificial intelligence winter."
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Neuroimaging Clin. N. Am. · Nov 2020
ReviewOverview of Machine Learning: Part 2: Deep Learning for Medical Image Analysis.
Deep learning has contributed to solving complex problems in science and engineering. This article provides the fundamental background required to understand and develop deep learning models for medical imaging applications. The authors review the main deep learning architectures such as multilayer perceptron, convolutional neural networks, autoencoders, recurrent neural networks, and generative adversarial neural networks. They also discuss the strategies for training deep learning models when the available datasets are imbalanced or of limited size and conclude with a discussion of the obstacles and challenges hindering the deployment of deep learning solutions in clinical settings.
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Neuroimaging Clin. N. Am. · Aug 2020
ReviewTechnical Improvements in Head and Neck MR Imaging: At the Cutting Edge.
Head and neck MR imaging is technically challenging because of magnetic field inhomogeneity, respiratory and swallowing motion, and necessity of high-resolution imaging to trace key anatomic structures. These challenges have been answered by advances in MR imaging technology, including isovolumetric three-dimensional imaging, robust fat-water separation techniques, and novel deep learning-based reconstruction algorithms. ⋯ Improvements in acquisition and reconstruction technique facilitate novel applications of morphologic and functional imaging. This results in opportunities to improve diagnosis, staging, and treatment selection through application of advanced MR imaging techniques.
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Neuroimaging Clin. N. Am. · Aug 2020
ReviewPET Imaging of Tumor Hypoxia in Head and Neck Cancer: A Primer for Neuroradiologists.
Tumor hypoxia is a known independent prognostic factor for adverse patient outcomes in those with head and neck cancer. Areas of tumor hypoxia have been found to be more radiation resistant than areas of tumor with normal oxygenation levels. ⋯ PET imaging is the gold standard method for imaging tumor hypoxia, with 18F-fluoromisonidazole the most extensively studied hypoxic imaging tracer. Newer tracers also show promise.