AdaRes: A deep learning‐based model for ultrasound image denoising: Results of image quality metrics, radiomics, artificial intelligence, and clinical studies
Ali Abbasian Ardakani,
Afshin Mohammadi,
Thomas J. Vogl
et al.
Abstract:PurposeThe quality of ultrasound images is degraded by speckle and Gaussian noises. This study aims to develop a deep‐learning (DL)‐based filter for ultrasound image denoising.MethodsA novel DL‐based filter using adaptive residual (AdaRes) learning was proposed. Five image quality metrics (IQMs) and 27 radiomics features were used to evaluate denoising results. The effect of our proposed filter, AdaRes, on four pre‐trained convolutional neural network (CNN) classification models and three radiologists was asse… Show more
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