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Abstract #2252

A dual-step iterative temperature estimation method for accurate and precise fat referenced PRFS temperature mapping

Chuanli Cheng1,2, Chao Zou1, Yangzi Qiao1, Changjun Tie1, Qian Wan1,2, Xin Liu1, and Hairong Zheng1

1Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, GuangDong, China, 2University of Chinese Academy of Sciences, Beijing, China

Temperature imaging based on proton resonance frequency shift (PRFS) fails in fat containing tissues as the proton frequency of fat does not change with temperature. A dual-step iterative temperature estimation of fat referenced PRFS method is proposed to improve both the accuracy and precision of fat-referenced PRFS method. The method is evaluated with fat-water phantom and ex vivo BAT tissue excised from rats. Compared to the existing methods, the proposed method has least bias to the fluorescent optical fiber thermometer while maintaining the best noise performance.

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