Abstract #2400

Feasibility Study of Improving SPIRiT by Exploiting Artificial Sparsity in Dynamic MRI

Jucheng Zhang¹, Zhikang Wang¹, Wenhong Ding², Xia Kong³, and Zhifeng Chen^4,5

¹2nd Affiliated Hospital, Zhejiang University, Hangzhou, China, ²Radiology, 2nd Affiliated Hospital, Zhejiang University, Hangzhou, China, ³School of Computer and Information Science, Hubei Engineering University, Xiaogan, China, ⁴School of Biomedical Engineering, Southern Medical University, Guangzhou, China, ⁵Guangdong Provincial Key Laboratory of Medical Image Processing, Guangzhou, China

Improving spatiotemporal resolution is of great importance for dynamic MRI in clinical circumstances. An improved SPIRiT method using artificial sparsity and PCA denoising is proposed in this work. Simulated cardiac perfusion phantom and in-vivo cardiac cine experiments were conducted. The proposed method showed better image quality compared with GRAPPA and the frame-by-frame SPIRiT method.

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