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Abstract #2168

Denoising arterial spin labeling cerebral blood flow images using deep learning-based methods

Danfeng Xie1, Li Bai1, and Ze Wang1,2

1Electrical and Computer Engineering, Temple university, Philadelphia, PA, United States, 2Department of Radiology, Temple university, Philadelphia, PA, United States

In this study, we use Deep Learning-based (DL) method to denoising ASL CBF images. Convolutional neural networks with a “wide” structure, residual learning and batch normalization are utilized as the core of our denoising model. Comparing to non-DL-based methods, the proposed method showed a significant SNR increase as well as partial volume effects improvement. Also, the DL-based method requires less CBF input images, which significantly shorten the acquisition time and reduce the chance of head motion.

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