An End-to-End AI-Based Framework for Automated Discovery of CEST/MT MR 
Fingerprinting Acquisition Protocols and Quantitative Deep Reconstruction 
(AutoCEST)

Perlman, O; Zhu, B; Zaiss, M; Rosen, MS; Farrar, CT

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An End-to-End AI-Based Framework for Automated Discovery of CEST/MT MR Fingerprinting Acquisition Protocols and Quantitative Deep Reconstruction (AutoCEST)

Perlman, O., Zhu, B., Zaiss, M., Rosen, M., & Farrar, C. (submitted). An End-to-End AI-Based Framework for Automated Discovery of CEST/MT MR Fingerprinting Acquisition Protocols and Quantitative Deep Reconstruction (AutoCEST).

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Item Permalink: http://hdl.handle.net/21.11116/0000-0008-E326-D Version Permalink: http://hdl.handle.net/21.11116/0000-000A-513D-7

Genre: Preprint

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https://arxiv.org/pdf/2107.04737.pdf (Any fulltext)

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Creators:
Perlman, O, Author
Zhu, B, Author
Zaiss, M^{1, 2}, Author
Rosen, MS, Author
Farrar, CT, Author

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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, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794

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Dates: Submitted: 2021-07

Publication Status: Submitted

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