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Abstract #0748

Harmonizing 2D and 3D FLAIR MRIs in white matter hyperintensity quantification

Yasheng Chen1, Chia-Ling Phuah1, Chunwei Ying2, Xing Dai1, Peter Kang1, Jin-Moo Lee1, Andria Ford1, and Hongyu An2
1Neurology, Washington University School of Medicine, St. Louis, MO, United States, 2Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States

Synopsis

Keywords: White Matter, White Matter, FLAIR, harmonization, white matter hyperintensity

Motivation: Harmonizing neural imaging datasets respectively acquired with 2D and 3D FLAIR MRI.

Goal(s): Converting 2D FLAIRs to high-resolution 3D FLAIRs.

Approach: We employed a ResUNet-based deep learning approach to learn the complex transformation from 2D to 3D FLAIR.

Results: The converted 3D FLAIRs bear a high resemblance to the acquired 3D FLAIR in terms of image similarity measures and white matter hyperintensity segmentation.

Impact: With this proposed approach, we can harmonize the 2D FLAIRs from the ADNI study with the 3D FLAIRs in the UK Biobank study.

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Keywords