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Abstract #4536

Application of Artificial Intelligence (AI)-assisted compressed sensing technology in ankle joint

Nan Wang1, Qingwei Song1, Ailian Liu1, Guobin Li2, Shuheng Zhang2, Yunfei Zhang3, and Yongming Dai3
1the First Affiliated Hospital of Dalian Medical University, Dalian, China, 2Shanghai United Imaging Healthcare Co., Ltd, Shanghai, China, 3MR Collaboration, Central Research Institute, United Imaging Healthcare, Shanghai, China

Synopsis

Keywords: Bone, JointsACS combines CS, half Fourier HF and parallel imaging (PI), and introduces deep learning neural network as AI module into the reconstruction process. Millions of fully sampled data are used to train AI models, so as to suppress various reconstruction artifacts introduced by traditional acceleration methods under high acceleration factors without affecting anatomy and pathological structures. ACS is used for noise suppression, artifact reduction and information recovery. ACS can effectively correct any major errors of single acceleration methods, thus providing a higher acceleration level for MRI imaging.

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Keywords