ABCnet: Adversarial bias correction network for infant brain MR images.
Ontology highlight
ABSTRACT: Automatic correction of intensity nonuniformity (also termed as the bias correction) is an essential step in brain MR image analysis. Existing methods are typically developed for adult brain MR images based on the assumption that the image intensities within the same brain tissue are relatively uniform. However, this assumption is not valid in infant brain MR images, due to the dynamic and regionally-heterogeneous image contrast and appearance changes, which are caused by the underlying spatiotemporally-nonuniform myelination process. Therefore, it is not appropriate to directly use existing methods to correct the infant brain MR images. In this paper, we propose an end-to-end 3D adversarial bias correction network (ABCnet), tailored for direct prediction of bias fields from the input infa
SUBMITTER: Chen L
PROVIDER: S-EPMC8316417 | biostudies-literature | 2021 Aug
REPOSITORIES: biostudies-literature
ACCESS DATA