Motion artifact in MRI images is the frequency existence in daily scanning and causes clinical distress. In this study, we proposed an automatic framework for MRI motion artifact detection using the residual features from neural network and spatial characteristics combination-based machine learning method, which can be applied to multiple body parts and sequences. High performance is achieved in validation with the accuracy of 97.6%. The comparison is performed with different representative methods and proving the effectiveness of the proposed architecture on limited dataset.
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