title: Combining Multi-atlas Segmentation with Brain Surface Estimation.
abstract: Whole brain segmentation (with comprehensive cortical and subcortical labels) and cortical surface reconstruction are two essential techniques for investigating the human brain. The two tasks are typically conducted independently, however, which leads to spatial inconsistencies and hinders further integrated cortical analyses. To obtain self-consistent whole brain segmentations and surfaces, FreeSurfer segregates the subcortical and cortical segmentations before and after the cortical surface reconstruction. However, this "segmentation to surface to parcellation" strategy has shown limitations in various situations. In this work, we propose a novel "multi-atlas segmentation to surface" method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. To our knowledge, this is the first work that achieves the reliability of state-of-the-art multi-atlas segmentation and labeling methods together with accurate and consistent cortical surface reconstruction. Compared with previous methods, MaCRUISE has three features: (1) MaCRUISE obtains 132 cortical/subcortical labels simultaneously from a single multi-atlas segmentation before reconstructing volume consistent surfaces; (2) Fuzzy tissue memberships are combined with multi-atlas segmentations to address partial volume effects; (3) MaCRUISE reconstructs topologically consistent cortical surfaces by using the sulci locations from multi-atlas segmentation. Two data sets, one consisting of five subjects with expertly traced landmarks and the other consisting of 100 volumes from elderly subjects are used for validation. Compared with CRUISE, MaCRUISE achieves self-consistent whole brain segmentation and cortical reconstruction without compromising on surface accuracy. MaCRUISE is comparably accurate to FreeSurfer while achieving greater robustness across an elderly population.
authors.affiliation: Electrical Engineering, Vanderbilt University, Nashville, TN.
authors.forename: Yuankai
authors.initials: Y
authors.lastname: Huo
authors.affiliation: Image Analysis and Communications Laboratory, Johns Hopkins University, Baltimore, MD.
authors.forename: Aaron
authors.initials: A
authors.lastname: Carass
authors.affiliation: Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD.
authors.forename: Susan M
authors.initials: SM
authors.lastname: Resnick
authors.affiliation: Center for Neuroscience and Regenerative Medicine, Henry Jackson Foundation, Bethesda, MD.
authors.forename: Dzung L
authors.initials: DL
authors.lastname: Pham
authors.affiliation: Image Analysis and Communications Laboratory, Johns Hopkins University, Baltimore, MD.
authors.forename: Jerry L
authors.initials: JL
authors.lastname: Prince
authors.affiliation: Electrical Engineering, Vanderbilt University, Nashville, TN.
authors.forename: Bennett A
authors.initials: BA
authors.lastname: Landman
keywords: Cerebral Cortex; Cortical Reconstruction; Magnetic Resonance Imaging; Multi-atlas Segmentation