568-01-013 ISMRM Abstract

MRIQC-Based Prediction of Ultra-Low-Field MRI Quality: A Random Forest Approach

Primary: Analysis Methods - Classification and Prediction

Secondary: Analysis Methods - Data Processing

568-01-013 · Unconventional Physics and Engineering · Wednesday, 13 May, 8:20 AM–9:15 AM · Digital Posters Row I

Keywords: Image Quality Assessment Automation Machine learning (ML)

Accepted

Hajer Karoui ¹, Niall J Bourke¹, Sean Deoni², Steven C Williams¹

¹Neuroimaging, Centre for Neuroimaging Sciences, King's College London, London, United Kingdom

²Maternal, Newborn, Child Nutrition and Health (MNCH) Discovery and Translational (D&T) Sciences Program, Gates Foundation, Seattle, United States of America

Presenting Author: Hajer Karoui

Synopsis

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References

1. Abate, F., Adu-Amankwah, A., Ae-Ngibise, K. A., Agbokey, F., Agyemang, V. A., Agyemang, C. T., ... & Williams, S. C. R. (2024). UNITY: A low-field magnetic resonance neuroimaging initiative to characterize neurodevelopment in low and middle-income settings. Developmental Cognitive Neuroscience, 69, 101397. https://doi.org/10.1016/j.dcn.2024.101397 [doi]

2. Deoni, S. C. L., Bruchhage, M. M. K., Beauchemin, J., Volpe, A., D’Sa, V., Huentelman, M., & Williams, S. C. R. (2021). Accessible pediatric neuroimaging using a low field strength MRI scanner. NeuroImage, 238, 118273. https://doi.org/10.1016/j.neuroimage.2021.118273 [doi]

3. Sheth, K. N., Mazurek, M. H., Yuen, M. M., Cahn, B. A., Shah, J. T., Ward, A., ... & Kimberly, W. T. (2021). Assessment of brain injury using portable, low-field magnetic resonance imaging at the bedside of critically ill patients. JAMA neurology, 78(1), 41-47. doi:10.1001/jamaneurol.2020.3263 [doi]

4. Turpin, J., Unadkat, P., Thomas, J., Kleiner, N., Khazanehdari, S., Wanchoo, S., ... & Schulder, M. (2020). Portable magnetic resonance imaging for ICU patients. Critical Care Explorations, 2(12), e0306. doi: 10.1097/CCE.0000000000000306 [doi]

5. Esteban, O., Birman, D., Schaer, M., Koyejo, O. O., Poldrack, R. A., & Gorgolewski, K. J. (2017). MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites. PloS one, 12(9), e0184661. doi: 10.1371/journal.pone.0184661 [doi]

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http://echo.ismrm.org/p/ISMRM2026/568-01-013