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 ...

Magnetic Resonance Imaging (MRI) has become an indispensable tool in the medical field for diagnosing and monitoring various diseases and conditions. However, the quality of MRI images can be degraded ...

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 ...

To ensure a fair comparison with Mostafa’s proposed CAE model, we maintained consistency in data processing, using T1-weighted MRI slice images of the healthy control group for autoencoder ...

The dataset is a compilation of CT scan images meant for studying COVID-19, but we are using it for the purpose of demonstrating denoising. Denoising using Autoencoder Autoencoder is a type of ...

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 ...

A self-supervised deep learning model has been developed to improve the quality of dynamic fluorescence images by leveraging temporal gradients. The method enables accurate denoising without ...