Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
431-03-001 / 431-03-001 ISMRM Abstract

When Noise Misleads: Understanding the Impact of Correlated Noise on Quantitative Image Quality Metrics in MRI

Accepted
Andrianna Scott 1, James Rioux1,2,3,4, Chris Bowen2,3, Kalei Crowell5, Steven Beyea1,2,3,4,6
1Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Canada
2Department of Diagnostic Radiology, Dalhousie University, Halifax, Canada
3Biomedical Translational Imaging Centre (BIOTIC), QEII Health Sciences Centre, Halifax, Canada
4School of Biomedical Engineering, Dalhousie University, Halifax, Canada
5Faculty of Medicine, Dalhousie University, Halifax, Canada
6IWK Health, Halifax, Canada
Presenting Author: Andrianna Scott

Synopsis

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References

1. White OA, Shur J, Castagnoli F, et al. Quantitative image quality metrics enable resource-efficient quality control of clinically applied AI-based reconstructions in MRI. Magma N Y N. 2025;38(3):547-560. doi:10.1007/s10334-025-01253-3 [doi]
2. Dietrich O, Raya JG, Reeder SB, Ingrisch M, Reiser MF, Schoenberg SO. Influence of multichannel combination, parallel imaging and other reconstruction techniques on MRI noise characteristics. Magn Reson Imaging. 2008;26(6):754-762. doi:10.1016/j.mri.2008.02.001 [doi]
3. Exposto Soares L, Brandão R, Borges L, Barufaldi B, Maidment A, Vieira M. Assessing the Impact of Correlated Noise in Digital Mammography: A Virtual Clinical Trial.; 2023. doi:10.1117/12.2654111 [doi]
4. LaMontagne PJ, Benzinger TL, Morris JC, et al. OASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer Disease. medRxiv. Preprint posted online December 15, 2019:2019.12.13.19014902. doi:10.1101/2019.12.13.19014902 [doi]
5. Kastryulin S, Zakirov J, Prokopenko D, Dylov DV. PyTorch Image Quality: Metrics for Image Quality Assessment. arXiv. Preprint posted online 2022. doi:10.48550/ARXIV.2208.14818 [doi]

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