Three-Dimensional Whole Breast Segmentation in Sagittal and Axial Breast MRI With Dense Depth Field Modeling and Localized Self-Adaptation for Chest-Wall Line Detection.

ABSTRACT:

Objective

Whole breast segmentation is an essential task in quantitative analysis of breast MRI for cancer risk assessment. It is challenging, mainly, because the chest-wall line (CWL) can be very difficult to locate due to its spatially varying appearance-caused by both nature and imaging artifacts-and neighboring distracting structures. This paper proposes an automatic three-dimensional (3-D) segmentation method, termed DeepSeA, of whole breast for breast MRI.

Methods

DeepSeA distinguishes itself from previous methods in three aspects. First, it reformulates the challenging problem of CWL localization as an equivalent problem that optimizes a smooth depth field and so fully utilizes the CWL's 3-D continuity. Second, it employs a localized self-adapting algorithm to adjust

SUBMITTER: Wei D 

PROVIDER: S-EPMC6684022 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature