The annual meeting of the Radiological Society of North America highlighted how artificial intelligence is being used to augment medical imaging.
RSNA 2020, the annual meeting of the Radiological Society of North America, showcases the latest research advances and product developments in all areas of radiology. Here’s a selection of studies presented at this year’s all-virtual event, all of which demonstrate the increasingly prevalent role played by artificial intelligence (AI) techniques in diagnostic imaging applications.
Deep-learning model helps detect TB
Early diagnosis of tuberculosis (TB) is crucial to enable effective treatments, but this can prove challenging for resource-poor countries with a shortage of radiologists. To address this obstacle, Po-Chih Kuo, from Massachusetts Institute of Technology, and colleagues have developed a deep-learning-based TB detection model. The model, called TBShoNet, analyses photographs of chest X-rays taken by a phone camera.
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