The presence of bias field inhomogeneity can negatively impact segmentation of breast fibroglandular tissue on MRI and subsequent quantification of background parenchymal enhancement. This can be particularly problematic in multi-center trials utilizing multiple imaging platforms. We have implemented the N4ITK algorithm for bias correction and evaluated the agreement between semi-automatic and semi-manual segmentation methods. Our results show that bias correction produces tissue segmentations and BPE estimates with better agreement with a reference manual segmentation method than non-corrected images.
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