Fully automated segmentation of whole breast using dynamic programming in dynamic contrast enhanced MR images

摘要

Purpose: Amount of fibroglandular tissue (FGT) and level of background parenchymal enhancement (BPE) in breast dynamic contrast enhanced magnetic resonance images (DCE-MRI) are suggested as strong indices for assessing breast cancer risk. Whole breast segmentation is the first important task for quantitative analysis of FGT and BPE in three-dimensional (3-D) DCE-MRI. The purpose of this study is to develop and evaluate a fully automated technique for accurate segmentation of the whole breast in 3-D fat-suppressed DCE-MRI.