Brain MRI artefact detection and correction using convolutional neural networks

Background and Objective: Brain MRI is one of the most commonly used diagnostic imaging tools to detect neurodegenerative disease. Diagnostic image quality is a key factor to enable robust image analysis algorithms developed for downstream tasks such as segmentation. In clinical practice, one of the main challenges is the presence of image artefacts, which can lead to low diagnostic image quality.