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WebNov 12, 2024 · Recently, deep learning approaches for MR motion artifact correction have been extensively studied. Although these approaches have shown high performance and reduced computational complexity compared to classical methods, most of them require supervised training using paired artifact-free and artifact-corrupted images, which may … WebJul 1, 2024 · The manuscript has been divided into different sections: section 2 elaborates on different types of artifacts commonly found in the EEG data. Section 3 briefed the … tavares the greatest hits
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WebRecently, deep learning approaches for MR motion artifact correction have been extensively studied. Although these approaches have shown high performance and lower … Generally speaking, an artifact (American English spelling) or artefact (British English spelling) is some unexpected or unwanted feature in the data that we acquired with our EEG or MEG system. Artifacts can be physiological or non-physiological in origin. An eyeblink is an example of a physiological artifact that shows … See more FieldTrip deals with artifacts by first identifying them, and subsequently removing them. Detection of artifacts can be done visually, or … See more Rather than excluding segments with artifacts, in some cases you can assume that the artifact is a linear addition to the signal of interest. If you arte able to identify the artifact, … See more With this strategy, pieces of data contaminated by artifacts are identified and removed from further analysis. For example, a bad channel is excluded, or trials with artifacts are removed. You may want to use this … See more Following this short introduction on dealing with artifacts in FieldTrip, you can continue with the visual artifact rejection and the automatic artifact rejection tutorials. More … See more WebNov 12, 2024 · Recently, deep learning approaches for MR motion artifact correction have been extensively studied. Although these approaches have shown high performance and … tavares the band