Analysis of Deep Learning-based Reconstruction Models for Highly Accelerated MR Cholangiopancreatography: to Fine-tune or not to Fine-tune

Kim J, Benkert T, Riemenschneider B, Nickel MD, Knoll F (2023)

Publication Type: Conference contribution, Abstract of a poster

Publication year: 2023

Conference Proceedings Title: Analysis of Deep Learning-baed Reconstruction Models for Highly Accelerated MR Cholangiopancreatography: to Fine-tune or not to Fine-tune

Event location: Toronto, ON CA

Authors with CRIS profile

Jinho Kim Professur für Computational Imaging Bruno Riemenschneider Professur für Computational Imaging Florian Knoll Professur für Computational Imaging

Involved external institutions

Siemens Healthineers DE Germany (DE)

How to cite

APA:

Kim, J., Benkert, T., Riemenschneider, B., Nickel, M.D., & Knoll, F. (2023, June). Analysis of Deep Learning-based Reconstruction Models for Highly Accelerated MR Cholangiopancreatography: to Fine-tune or not to Fine-tune. Poster presentation at 2023 ISMRM & ISMRT Annual Meeting & Exhibition, Toronto, ON, CA.

MLA:

Kim, Jinho, et al. "Analysis of Deep Learning-based Reconstruction Models for Highly Accelerated MR Cholangiopancreatography: to Fine-tune or not to Fine-tune." Presented at 2023 ISMRM & ISMRT Annual Meeting & Exhibition, Toronto, ON 2023.

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