Noise reduction by multiple path neural network using Attention mechanisms with an emphasis on robustness against Errors: A pilot study on brain Diffusion-Weighted images

Improving the signal-to-noise ratio has always been a major challenge in the history of magnetic resonance imaging (MRI). Recently, deep learning-based image noise reduction has attracted attention as a promising technique for this purpose [1 –3]. The methods found a relationship between noisy images and noise-free images by combining the high approximation ability of neural networks and the high optimisation ability of deep learning in the ‘training’ process. This relationship, incorporated in the trained model, is used to reduce image noise.

Source: Physica Medica: European Journal of Medical Physics - November 21, 2023 Category: General Medicine Authors: Yasuhiko Tachibana, Yujiro Otsuka, Hayato Nozaki, Koji Kamagata, Shinichiro Mori, Yuya Saito, Shigeki Aoki Tags: Technical Note Source Type: research