Clinical imaging
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Artificial intelligence (AI) is a fast-growing research area in computer science that aims to mimic cognitive processes through a number of techniques. Supervised machine learning, a subfield of AI, includes methods that can identify patterns in high-dimensional data using labeled 'ground truth' data and apply these learnt patterns to analyze, interpret, or make predictions on new datasets. Supervised machine learning has become a significant area of interest within the medical community. ⋯ One devastating disease for which neuroimaging plays a significant role in the clinical management is stroke. Within this context, AI techniques can play pivotal roles for image-based diagnosis and management of stroke. This overview focuses on the recent advances of artificial intelligence methods - particularly supervised machine learning and deep learning - with respect to workflow, image acquisition and reconstruction, and image interpretation in patients with acute stroke, while also discussing potential pitfalls and future applications.
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The chest computed tomography (CT) features of coronavirus disease 2019 (COVID-19) and Streptococcus pneumoniae pneumonia (S. pneumoniae pneumonia) were compared to provide further evidence for the differential imaging diagnosis of patients with these two types of pneumonia. ⋯ The findings of GGO, the crazy paving sign, and abnormally thickened interlobular septa on chest CT were significantly higher in COVID-19 than S. pneumoniae pneumonia. The most important differential points on chest CT signs between COVID-19 and S. pneumoniae pneumonia were whether disease lesions were distributed in entire lung lobes and segments and whether the crazy paving sign, interlobular septal thickening, and consolidation lesions were found.
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The coronavirus disease 2019 (COVID-19) outbreak, first reported in Wuhan, China, is gradually spreading worldwide. For diagnosis, chest computed tomography is a conventional, noninvasive imaging modality that is very accurate for detection and evaluation of pneumonia and is an important adjunct to real-time reverse transcription polymerase chain reaction diagnosis of the virus. Previous studies have reported typical computed tomography imaging features indicative of COVID-19, such as multifocal ground-glass opacities with or without consolidation. ⋯ Thus, advanced training and education in standardized infection control and prevention practice are essential. The purpose of this brief review is to summarize such training and education for clinical management of this outbreak for radiology department personnel. We will describe standard transmission-based precautions, workflow for computed tomography examination of fever patients, and decontamination management of a radiology department.
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Coronavirus disease 2019 (COVID-19), a clinical manifestation of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was declared a global pandemic by the World Health Organization on March 11, 2020. Hypercoagulable state has been described as one of the hallmarks of SARS-CoV-2 infection and has been reported to manifest as pulmonary embolisms, deep vein thrombosis, and arterial thrombosis of the abdominal small vessels. Here we present cases of arterial and venous thrombosis pertaining to the head and neck in COVID-19 patients.
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Typical chest CT findings in COVID-19 have been described as bilateral peripheral ground glass opacities, with or without consolidation. Halo sign and reversed halo sign have been reported as atypical imaging findings in this disease. However, to the best of our knowledge, combined presence of these signs has never been reported before. Herein, we present a COVID-19 patient with numerous atypical target-shaped, combined halo and reversed halo pulmonary lesions, in the absence of any other underlying disease.