Researchers conducted a study on neck CT scans of patients with suspected neck tumors, using different radiation doses and denoising software to assess image quality. They found that denoised datasets had lower image noise and higher contrast-to-noise ratio compared to original scans at different dose levels. Radiologists rated denoised images higher in quality, sharpness, and contrast than original scans at 100% and 50% of conventional doses. The study suggested that using denoising algorithms could help reduce radiation exposure, especially in younger patients at risk of radiation-induced malignancies. The findings indicate that denoising can maintain high image quality even at lower radiation doses, potentially benefiting patients undergoing repeated scans. The study abstract is available for further reading.
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Source link: https://healthimaging.com/topics/medical-imaging/computed-tomography-ct/deep-learning-denoising-software-can-cut-radiation-exposure-25-conventional-doses-during-neck-ct
#Reduced radiation exposure with deep learning denoising software #DeepLearning
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