Attention-gated convolutional neural networks for off-resonance correction of spiral real-time MRI

• URL: http://arxiv.org/abs/2102.07271v1
• Date: Sun, 14 Feb 2021 23:43:50 GMT
• Title: Attention-gated convolutional neural networks for off-resonance correction of spiral real-time MRI
• Authors: Yongwan Lim, Shrikanth S. Narayanan, Krishna S. Nayak
• Abstract summary: We present a new CNN-based off-resonance correction method that incorporates an attention-gate mechanism. We demonstrate improved performance with the attention-gate, on 1.5 Tesla spiral speech RT-MRI, compared to existing off-resonance correction methods.
• Score: 58.11266896200967
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Spiral acquisitions are preferred in real-time MRI because of their efficiency, which has made it possible to capture vocal tract dynamics during natural speech. A fundamental limitation of spirals is blurring and signal loss due to off-resonance, which degrades image quality at air-tissue boundaries. Here, we present a new CNN-based off-resonance correction method that incorporates an attention-gate mechanism. This leverages spatial and channel relationships of filtered outputs and improves the expressiveness of the networks. We demonstrate improved performance with the attention-gate, on 1.5 Tesla spiral speech RT-MRI, compared to existing off-resonance correction methods.

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