Automated Multiclass Artifact Detection in Diffusion MRI Volumes via 3D Residual Squeeze-and-Excitation Convolutional Neural Networks

Automated Multiclass Artifact Detection in Diffusion MRI Volumes via 3D Residual Squeeze-and-Excitation Convolutional Neural Networks

Diffusion MRI (dMRI) is widely used to investigate neuronal and structural development of brain. dMRI data is often contaminated with various types of artifacts. Hence, artifact type identification in dMRI volumes is an essential pre-processing step prior to carrying out any further analysis. Manual...

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Bibliographic Details
Main Authors: Nabil Ettehadi, Pratik Kashyap, Xuzhe Zhang, Yun Wang, David Semanek, Karan Desai, Jia Guo, Jonathan Posner, Andrew F. Laine
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-03-01
Series:Frontiers in Human Neuroscience
Subjects:
diffusion MRI
artifacts
quality control
convolutional neural networks
deep learning
medical imaging
Online Access:https://www.frontiersin.org/articles/10.3389/fnhum.2022.877326/full

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