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  Linear projection-based CEST reconstruction: the simplest explainable AI

Glang, F., Fabian, M., German, A., Khakzar, K., Mennecke, A., Laun, F., et al. (2021). Linear projection-based CEST reconstruction: the simplest explainable AI. Poster presented at 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021).

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Glang, F1, 2, Author              
Fabian, M, Author
German, A, Author
Khakzar, K, Author
Mennecke, A, Author
Laun, F, Author
Kasper, B, Author
Schmidt, M, Author
Doerfler, A, Author
Scheffler, K1, 2, Author              
Zaiss, M1, 2, Author              
Affiliations:
1Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: Evaluation of multi-parametric in vivo CEST MRI often requires complex computational processing for both field inhomogeneity correction and contrast generation. In this work, linear regression was used to obtain coefficient vectors that directly map uncorrected 7T spectra to corrected Lorentzian target parameters by simple linear projection. The method generalizes from healthy subject training data to unseen test data of both healthy subjects and tumor patients. The linear projection approach thus integrates correction of both B0 and B1 inhomogeneity as well as contrast generation in a single fast and interpretable computation step.

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 Dates: 2021-05
 Publication Status: Published online
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Title: 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021)
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Start-/End Date: 2021-05-15 - 2021-05-20

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Title: 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 1454 Start / End Page: - Identifier: -