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. Author manuscript; available in PMC: 2020 Oct 1.
Published in final edited form as: J Magn Reson Imaging. 2019 Jul 5;52(4):998–1018. doi: 10.1002/jmri.26852

FIGURE 2:

FIGURE 2:

Automatic breast segmentation pipeline incorporating machine learning. Axial T1-weighted precontrast images are automatically segmented at breast-air (blue) and breast-chest wall (red) boundary (a). Breast is further subdivided into fibroglandular breast tissue (FGT, green) and fat. Background parenchymal enhancement (BPE) is calculated as FGT enhancement over baseline and is 12% (minimal) in this 66-year-old screening patient, as demonstrated on the first postcontrast subtraction images (b).