Artificial intelligence for point of care radiograph quality assessment

Abstract
Chest X-rays are among the most common modalities in medical imaging. Technical flaws of these images, such as over- or under-exposure or wrong positioning of the patients can result in a decision to reject and repeat the scan. We propose an automatic method to detect images that are not suitable for diagnostic study. If deployed at the point of image acquisition, such a system can warn the technician, so the repeat image is acquired without the...
Paper Details
Title
Artificial intelligence for point of care radiograph quality assessment
Published Date
Mar 13, 2019
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