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Abstract #3362

Myelin Water Imaging using Dimensionality Reduction

Jae Eun Song1, Shreyas Vasanawala2, and Dong-Hyun Kim3
1Radiology, Stanford University, Stanford, CA, United States, 2Department of Radiology, Stanford University, Stanford, CA, United States, 3Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea, Republic of


Multi-echo gradient-echo (mGRE)-based myelin water fraction (MWF) mapping is a promising myelin water imaging (MWI) modality but is vulnerable to noise and artifact corruption. The linear dimensionality reduction (LDR) method has recently shown improvements with regard to these challenges. However, the magnitude value based low rank operators have been shown to misestimate the MWF for regions with T2* anisotropy. This paper presents a nonlinear dimensionality reduction (NLDR) method to estimate the MWF map better by encouraging nonlinear low dimensionality of mGRE signal sources.

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