TY - GEN
T1 - Improved quantification of chemical exchange saturation transfer (CEST) MRI using nonlocal means
AU - Yuan, Jing
AU - Mok, Greta Seng Peng
AU - Zhang, Qinwei
AU - Wang, Yi Xiang
AU - Zhou, Jinyuan
N1 - Funding Information:
Manuscript received November 15, 2014. This work was supported by Hong Kong RGC grant SEGCUHK02, CUHK418811, China NSFC grant 81201076, Univ. of Macau research grant MYRG185(Y4-L3)-FST11-MSP, USA NIH grants R01EB009731, R01CA166171.
Publisher Copyright:
© 2014 IEEE.
PY - 2016/3/10
Y1 - 2016/3/10
N2 - Chemical exchange saturation transfer (CEST) MRI offers a powerful molecular imaging tool by exploiting the proton exchanges between free water and labile exchangeable molecules in vivo. Accurate CEST quantification from Z-spectrum analysis, particularly at clinical field strengths, suffers from low contrast-to-noise ratio (CNR). In this study, we proposed the use of non-local means (NLM) for CEST-MRI denoising to improve the CEST contrast quantification. The experimental results showed that the NLM denoising effectively removed noise presented in the low signal-to-noise ratio (SNR) CEST images with high resolution and well preserved the tissue structures. The CEST contrast map generated from the NLM-denoised images was notably improved, which was closer to the map generated from images with 3.5-fold higher SNR and meanwhile had much less partial volume effect. NLM denoising holds great potentials for the clinical CEST-MRI quantification improvement without compromising spatial resolution.
AB - Chemical exchange saturation transfer (CEST) MRI offers a powerful molecular imaging tool by exploiting the proton exchanges between free water and labile exchangeable molecules in vivo. Accurate CEST quantification from Z-spectrum analysis, particularly at clinical field strengths, suffers from low contrast-to-noise ratio (CNR). In this study, we proposed the use of non-local means (NLM) for CEST-MRI denoising to improve the CEST contrast quantification. The experimental results showed that the NLM denoising effectively removed noise presented in the low signal-to-noise ratio (SNR) CEST images with high resolution and well preserved the tissue structures. The CEST contrast map generated from the NLM-denoised images was notably improved, which was closer to the map generated from images with 3.5-fold higher SNR and meanwhile had much less partial volume effect. NLM denoising holds great potentials for the clinical CEST-MRI quantification improvement without compromising spatial resolution.
UR - http://www.scopus.com/inward/record.url?scp=84965082237&partnerID=8YFLogxK
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U2 - 10.1109/NSSMIC.2014.7430844
DO - 10.1109/NSSMIC.2014.7430844
M3 - Conference contribution
AN - SCOPUS:84965082237
T3 - 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014
BT - 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014
Y2 - 8 November 2014 through 15 November 2014
ER -