Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on pattern recogniti on and artificial intelligence are discussed in a new report. According to news reporting from Shanghai, People's Republic of China, by NewsRx journalists, rese arch stated, "Medical images are susceptible to noise and artifacts, so denoisin g becomes an essential pre-processing technique for further medical image proces sing stages." The news reporters obtained a quote from the research from University of Shangha i for Science and Technology: "We propose a medical image denoising method based on dual-attention mechanism for generative adversarial networks (GANs). The met hod is based on a GAN model with fused residual structure and introduces a globa l skip-layer connection structure to balance the learning ability of the shallow and deep networks. The generative network uses a residual module containing cha nnel and spatial attention for efficient extraction of CT image features. The me an square error loss and perceptual loss are introduced to construct a composite loss function to optimize the model loss function, which helps to improve the i mage generation effect of the model. Experimental results on the LUNA dataset an d "the 2016 Low-Dose CT Grand Challenge" dataset show that DAGAN achieves the be st results in root mean square error (RMSE), structural similarity (SSIM) and pe ak signal-to-noise ratio (PSNR) when compared to the state-of-the-art methods."
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