The denoising neural network (dnCNN) found in the Deep Learning ... Image.The Wiener filter was of a kernel size of (5,5) This was an inbuilt OpenCV method for denoising images. This was also tried ...

In recent years, machine learning techniques have shown great potential in enhancing the accuracy of image denoising, especially in the medical domain. In this study, we propose a novel deep learning ...

Both networks are compared against a state-of-the-art algorithm, Non-Local Means (NLM) using ... learning or unsupervised and self-supervised strategies must be employed. As such, we evaluate ...

This study aims to explore an autoencoder-based method for generating ... relying solely on expert manual analysis of MRI images has its limitations. Thus, the use of deep learning technologies for ...

For example, in medical images like X-rays, MRI, CT scans ... images meant for studying COVID-19, but we are using it for the purpose of demonstrating denoising. Autoencoder is a type of unsupervised ...

In PhotoniX, researchers report a self-supervised deep learning method ... adaptively adjusts the use of temporal redundancy for denoising. By processing time-lapse image sequences with this ...

In a recent study published in the journal Science Advances, researchers described a deep learning ... their brain images on the 0.055 T MRI scanner. Data were reconstructed using PF-SR as ...