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Abstract #2779

Improved image quality of liver diffusion-weighted imaging by combining compressed sensing and sensitivity encoding

Naoki Ohno1, Satoshi Kobayashi1, Tosiaki Miyati1, Yu Ueda2, Masami Yoneyama2, and Toshifumi Gabata1
1Kanazawa University, Kanazawa, Japan, 2Philips Japan, Tokyo, Japan

Although sensitivity encoding (SENSE) technique is commonly used to reduce distortion in diffusion-weighted imaging (DWI), highly accelerated SENSE results in significantly increased noise, leading to systematic errors to the quantification of apparent diffusion coefficient. In this study, we proposed a novel method using compressed sensing combined with a highly accelerated sensitivity encoding (CS-SENSE) to reduce both the distortion and noise in liver DWI. The CS-SENSE demonstrated the higher SNR and reduced geometric distortion compared with conventional SENSE reconstruction. Liver DWI with the proposed method can improve the image quality with better lesion conspicuity.

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