Abstract #3725
Automatic identification of motion in multishot MRI using convolutional neural networks
Shayan Guhaniyogi 1 , Mei-Lan Chu 1 , and Nan-Kuei Chen 1
1
Brain Imaging and Analysis Center, Duke
University, Durham, NC, United States
A major concern of multishot MRI acquisitions is the
effect of subject motion, which can result in
undesirable image artifacts. In order to discard or
correct these images, the first step is to identify the
images which have been corrupted. We describe an
automated machine-learning method to identify
motion-corrupted multishot images using unsupervised
feature learning and a convolutional neural network. We
demonstrate that the method can accurately classify
motion-corrupted images of different contrasts and
different multishot acquisition types. The result is an
effective technique which eliminates the need for manual
identification of motion artifacts in multishot images.
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