Synopsis
Motivation:
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460-02-008
ISMRM Abstract
Detectability of white matter hyperintensities in 0.6T FLAIR scans
Accepted
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1. Campbell-Washburn AE, Ramasawmy R, Restivo MC, et al. Opportunities in Interventional and Diagnostic Imaging by Using High-Performance Low-Field-Strength MRI. Radiology. 2019;293(2):384-393. doi:10.1148/radiol.2019190452 [doi]
2. Arnold TC, Freeman CW, Litt B, Stein JM. Low‐field MRI: Clinical promise and challenges. Magnetic Resonance Imaging. 2023;57(1):25-44. doi:10.1002/jmri.28408 [doi]
3. Marques JP, Simonis FFJ, Webb AG. Low‐field MRI: An MR physics perspective. J Magn Reson Imaging. 2019;49(6):1528-1542. doi:10.1002/jmri.26637 [doi]
4. Jabarimani N, Ercan E, Dong Y, et al. Characterizing differences between white and gray matter T W-based segmentations at 0.6 T and 1.5 T.
5. Bachmann R, Reilmann R, Schwindt W, Kugel H, Heindel W, Krämer S. FLAIR imaging for multiple sclerosis: a comparative MR study at 1.5 and 3.0 Tesla. Eur Radiol. 2006;16(4):915-921. doi:10.1007/s00330-005-0070-8 [doi]
6. Ghaznawi R, Geerlings MI, Jaarsma-Coes M, Hendrikse J, De Bresser J, on behalf of the UCC-Smart Study Group F.L.J. Visseren MD, PhD F.W. Asselbergs MD, PhD H.M. Nathoe MD, PhD M.L. Bots MD, PhD M.H. Emmelot MD, PhD G.J. de Borst MD, PhD L.J. Kappelle MD, PhD T. Leiner MD, PhD P.A. de Jong MD, PhD A.T. Lely MD, PhD N.P. van der Kaaij MD, PhD Y. Ruigrok MD, PhD M.C. Verhaar MD, PhD J. Westerink MD, PhD. Association of White Matter Hyperintensity Markers on MRI and Long-term Risk of Mortality and Ischemic Stroke: The SMART-MR Study. Neurology. 2021;96(17). doi:10.1212/WNL.0000000000011827 [doi]
7. Keller JA, Sigurdsson S, Klaassen K, et al. White matter hyperintensity shape is associated with long‐term dementia risk. Alzheimer’s & Dementia. 2023;19(12):5632-5641. doi:10.1002/alz.13345 [doi]
8. Heinen R, Steenwijk MD, Barkhof F, et al. Performance of five automated white matter hyperintensity segmentation methods in a multicenter dataset. Sci Rep. 2019;9(1):16742. doi:10.1038/s41598-019-52966-0 [doi]
9. Wiltgen T, McGinnis J, Schlaeger S, et al. LST-AI: A deep learning ensemble for accurate MS lesion segmentation. NeuroImage: Clinical. 2024;42:103611. doi:10.1016/j.nicl.2024.103611 [doi]
10. Duering M, Biessels GJ, Brodtmann A, et al. Neuroimaging standards for research into small vessel disease—advances since 2013. The Lancet Neurology. 2023;22(7):602-618. doi:10.1016/S1474-4422(23)00131-X [doi]
11. Wardlaw JM, Smith EE, Biessels GJ, et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. The Lancet Neurology. 2013;12(8):822-838. doi:10.1016/S1474-4422(13)70124-8 [doi]
12. Ashburner J, Friston K. CHAPTER 4 - Rigid Body Registration. In: FRISTON K, ASHBURNER J, KIEBEL S, NICHOLS T, PENNY W, eds. Statistical Parametric Mapping. Academic Press; 2007:49-62. doi:10.1016/B978-012372560-8/50004-8 [doi]
13. Klein S, Staring M, Murphy K, Viergever MA, Pluim J. elastix: A Toolbox for Intensity-Based Medical Image Registration. IEEE Trans Med Imaging. 2010;29(1):196-205. doi:10.1109/TMI.2009.2035616 [doi]
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http://echo.ismrm.org/p/ISMRM2026/460-02-008