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AI system may help with mammographic breast positioning



A team led by Haruyuki Watanabe, PhD, from Gunma Prefectural College of Health Sciences in Maebashi found that their DCNN method had moderate accuracy when it came to breast positioning classification and nipple profile.

“The results of this study suggest that DCNNs can be used to classify mammographic breast positioning to evaluate imaging accuracy,” Watanabe and colleagues wrote. “The recognition of positioning criteria accuracy provides feedback to radiological technologists and can contribute to improving the accuracy of mammographic techniques.”

Previous research suggests that…


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Radiology AI
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