Reperforming imaging is a common problem when acquiring knee X-rays, draining unnecessary resources and exposing patients to added radiation. But experts have developed an artificial intelligence tool they believe can help.
A group of researchers from Osaka University in Japan unveiled their deep convolutional neural network Thursday in Radiography. The system assists technologists by classifying tilting direction errors and guiding correct positioning during lateral knee radiographs.
Many attempts have been made to reduce retake rates, but this tool focuses on correcting rejected images to cut down the number and time required to retake images. And initial experiments proved successful.
“Our research is a novel attempt to create a retaking support system,” Y. Ohta, with Osaka City University Hospital’s preventative medicine division, and colleagues explained. “This may reduce the inconvenience of patients and improve the work efficiency of radiological technologists, and we also assume that the proposed system may be used for the assistance and training for inexperienced radiological technologists and students.”
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June 05, 2021 at 12:42AM
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Support system helps technologists correct knee X-ray errors, reducing exam retake rates - Health Imaging
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