560-04-015 ISMRM Abstract

Supervised Residual U-Net for Pixel-wise Principal Strain Mapping from Cine SSFP Using Physics-Based Training Data

Primary: Cardiovascular - Myocardium

Secondary: Analysis Methods - Visualization

560-04-015 · Automated Cardiovascular MRI · Wednesday, 13 May, 2:35 PM–3:30 PM · Digital Posters Row A

Keywords: Deep learning Feature tracking Deep Learning in Medical Imaging Cine-MRI Cardiac function quantification

Accepted

Ahmed Hassan^1,2, Osama Mahmoud^1,2, Muhannad Abdallah², Ali S Badran², Mishkat Habib ³, Tamer Y Basha², Ahmed Gharib³, Ahmed Abdelfadeel³, Khaled Z Abd-Elmoniem³

¹Department of Applied Computer Science, Norwegian University of Science and Technology NTNU, Norway

²Systems and Biomedical Engineering Department, Faculty of Engineering, Cairo University, Giza, Egypt

³Biomedical and Metabolic Imaging Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, United States of America

Presenting Author: Mishkat Habib

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References

1. Scatteia A, Ferrara F, Bucciarelli Ducci C. State of the art myocardial strain by CMR feature tracking. Eur Radiol.2022;32:2371–2382. DOI: 10.1007/s00330-022-08629-2 [doi]

2. Schuster A, Hor KN, Kowallick JT, Beerbaum P, Kutty S. Cardiovascular Magnetic Resonance Myocardial Feature Tracking: Concepts and Clinical Applications. Circulation: Cardiovascular Imaging (2016) 9(4):e004077. DOI: 10.1161/CIRCIMAGING.115.004077 [doi]

3. Rajiah P, Kalisz K, et al., Myocardial Strain Evaluation with Cardiovascular MRI: Physics, Principles, and Clinical Applications. Radiographics. 2022;42(4). https://doi.org/10.1148/rg.210174 [doi]

4. Ronneberger O, Fischer P, Brox T. U Net: Convolutional networks for biomedical image segmentation. MICCAI.2015:234–241. https://doi.org/10.1007/978-3-319-24574-4_28 [doi]

5. Isensee F, Jaeger PF, Kohl SAA, Petersen J, Maier Hein KH. nnU Net: a self configuring method for biomedical segmentation. Nat Methods. 2021;18:203–211. https://doi.org/10.1038/s41592-020-01008-z [doi]

6. Project MONAI. MONAI Label: A framework for AI‑assisted Interactive Labeling of 3D Medical Images. arXiv:2203.12362 (2022). https://doi.org/10.48550/arXiv.2203.12362 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/560-04-015