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Abstract #4660

A combined application of Deep Learning Recon and MRI mute technique

Hongbin Wang1, Weinan Tang1, Jianghua Wu2, and Wei Xi2
1Beijing Wandong Medical Technology Co., Ltd, Beijing, China, 2intelligent perception institute, Midea Corporate Research Center, Shanghai, China

Synopsis

Keywords: AI/ML Image Reconstruction, Machine Learning/Artificial Intelligence, mute, acoustic reduction, Deep learning

Motivation: MRI mute technique reduces scanning noise by lowering the gradient slew rate which increase echo spacing, resulting in image blurring and longer scan time.

Goal(s): To design a scanning method that simultaneously reduces scan time and scanning noise without compromising image SNR and clarity.

Approach: Develop a DL-Recon post-processing model to enhance SNR and clarity of images which are acquired from optimized knee scanning protocol with mute technique.

Results: The proposed scanning method improves SNR about 38% and reduces scan time and noise sound pressure separately about 44.8% and 86%.

Impact: Combining DL-Recon with mute sequences help doctors to diagnose more patients. It also enhances the success of clinical scans by decreasing scan noise to improve patient comfort. This is a successful application of DL-Recon with mute scanning technique.

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