Deep neural networks-based denoising models for CT imaging and their efficacy

no code implementations • 18 Nov 2021 • Prabhat KC, Rongping Zeng, M. Mehdi Farhangi, Kyle J. Myers

These metrics are employed to perform a more nuanced study of the resolution of the DNN outputs' low-contrast features, their noise textures, and their CT number accuracy to better understand the impact each DNN algorithm has on these underlying attributes of image quality.

Image Denoising SSIM