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  Nonlinear Dimensionality Reduction for Magnetic Resonance Fingerprinting with Applications to Partial Volume

McGivney, D., Deshmane, A., Jiang, Y., Ma, D., & Griswold, M. (2015). Nonlinear Dimensionality Reduction for Magnetic Resonance Fingerprinting with Applications to Partial Volume. Poster presented at 23rd Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2015), Toronto, ON, Canada.

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http://archive.ismrm.org/2015/3380.html (Publisher version)
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McGivney, D, Author
Deshmane, A1, Author              
Jiang, Y, Author
Ma, D, Author
Griswold, M, Author
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1External Organizations, ou_persistent22              

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 Abstract: Magnetic resonance fingerprinting (MRF) is a technique that can provide quantitative maps of tissue parameters such as T1 and T2 relaxation times through matching observed signals to a precomputed complex-valued dictionary of modeled signal evolutions. Since each dictionary entry is uniquely defined by two real parameters, specifically T1 and T2, we propose to compress the dictionary onto a real-valued manifold of three dimensions using the nonlinear dimensionality reduction technique of kernel principal component analysis. Once the compression is achieved, we explore new computational applications for MRF, namely solving the partial volume problem.

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 Dates: 2015-05
 Publication Status: Published in print
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Title: 23rd Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2015)
Place of Event: Toronto, ON, Canada
Start-/End Date: 2015-05-30 - 2015-05-31

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Title: 23rd Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2015)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 3380 Start / End Page: - Identifier: -