Deep learning based correction of RF field induced inhomogeneities for T2w prostate imaging at 7 T
Seb D. Harrevelt,
Ettore F. M. Meliado,
Astrid L. H. M. W. van Lier
et al.
Abstract:At ultrahigh field strengths images of the body are hampered by B1‐field inhomogeneities. These present themselves as inhomogeneous signal intensity and contrast, which is regarded as a “bias field” to the ideal image. Current bias field correction methods, such as the N4 algorithm, assume a low frequency bias field, which is not sufficiently valid for T2w images at 7 T. In this work we propose a deep learning based bias field correction method to address this issue for T2w prostate images at 7 T. By combining… Show more
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