AAPM | COMP Joint Meeting · Vancouver · July 19-22
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To evaluate a commercial deep learning denoising algorithm (ClariCT.AI) through quantitative phantom measurements and clinical image assessment.
To evaluate the performance of a commercial deep-learning denoising algorithm (ClariCT.AI) for noise reduction and contrast-to-noise ratio (CNR) improvement in abdominal CT images with small hepatic cysts and lesions.
Accurate auto-contouring is essential for efficient prostate radiotherapy, particularly in image-guided and adaptive workflows, where contour quality influences clinical decision-making. This study quantitatively evaluates Radfor...
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