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Nykänen, Olli; Isosalo, Antti; Inkinen, Satu; Casula, Victor; Nevalainen, Mika; et al. (2022) Deep-Learning-based contrast synthesis from MRF parameter maps in the knee. Published in Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting (ISMRM 2022), 07-12 May 2022, London, England, UK, article number 0097, https://archive.ismrm.org/2022/0097.html

Deep-learning-based contrast synthesis from MRF parameter maps in the knee

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Author: Nykänen, Olli1,2; Isosalo, Antti1; Inkinen, Satu1;
Organizations: 1Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Finland
2Department of Applied Physics, University of Eastern Finland, Finland
3Medical Research Center, University of Oulu and Oulu University Hospital, Oulu
4Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
5Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
6Centre for Advanced Imaging, Queensland University, Brisbane, Australia
Format: abstract
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.5 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2023063068891
Language: English
Published: Society of Magnetic Resonance, 2022
Publish Date: 2023-06-30
Description:

Synopsis

In this study, deep convolutional neural networks (DCNN) are used to synthesize contrast-weighted magnetic resonance (MR) images from quantitative parameter maps of the knee joint obtained with magnetic resonance fingerprinting (MRF). Training of the neural networks was performed using data from 142 patients, for which both standard MR images and quantitative MRF maps of the knee were available. The study demonstrates that synthesizing contrast-weighted images from MRF-parameter maps is possible utilizing DCNNs. Furthermore, the study indicates a need to tune up the dictionary used in MRF so that the parameters expected from the target anatomy are well-covered.

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Series: Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
ISSN: 1524-6965
ISSN-E: 1545-4428
ISSN-L: 1524-6965
Article number: 0097
Host publication: Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting (ISMRM 2022)
Conference: Annual Meeting of International Society for Magnetic Resonance in Medicine
Field of Science: 113 Computer and information sciences
114 Physical sciences
217 Medical engineering
Subjects:
Abstract
Copyright information: © International Society for Magnetic Resonance in Medicine (ISMRM), Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting (ISMRM 2022). Published in this repository with the kind permission of the publisher.