Abstract #3208

MR ARTS-GROWL: A Non-Iterative Motion-Resistant Technique for High Spatiotemporal Liver DCE Imaging

Zhifeng Chen¹, Liyi Kang¹, Zhongbiao Xu², Chenguang Zhao³, Feng Huang⁴, Feng Liu⁵, and Ling Xia^1,6

¹Department of Biomedical Engineering, Zhejiang University, Hangzhou, People's Republic of China, ²School of Biomedical Engineering, Guangdong Provincial Key Laborary of Medical Image Processing, Southern Medical University, Guangzhou, People's Republic of China, ³Philips Healthcare (Suzhou) Co. Ltd., Suzhou, People's Republic of China, ⁴Neusoft Medical, Shanghai, China, ⁵School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia, ⁶State Key Lab of CAD&CG, Zhejiang University, Hangzhou, People's Republic of China

Motion, mainly caused by respiration, is an unavoidable problem in abdomen MR imaging, which often leads to image blurring and edge ghosting. We propose to combine motion-sorted information with dynamic artificial sparsity approach for radial dynamic contrast-enhanced (DCE) MR imaging. The results demonstrate that better image quality including SNR and low image bluring and more diagnostic information can be generated compared to non-motion-resistant scheme incorporated method.

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