@inproceedings{0e8df11a6773496b8e35d08ca8230273,
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 limitation 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.",
keywords = "Cerebral Cortex, Cortical Reconstruction, Magnetic Resonance Imaging, Multi-atlas Segmentation",
author = "Yuankai Huo and Aaron Carass and Resnick, {Susan M.} and Pham, {Dzung L.} and Prince, {Jerry L.} and Landman, {Bennett A.}",
note = "Funding Information: This research was supported by NSF CAREER 1452485, NIH 5R21EY024036, NIH 1R21NS064534, NIH 2R01EB006136, NIH 1R03EB012461, NIH R01EB006193, NIH 5R01NS056307, 5R21NS082891 Publisher Copyright: {\textcopyright} 2016 SPIE.; Medical Imaging 2016: Image Processing ; Conference date: 01-03-2016 Through 03-03-2016",
year = "2016",
doi = "10.1117/12.2216604",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Styner, {Martin A.} and Angelini, {Elsa D.} and Angelini, {Elsa D.}",
booktitle = "Medical Imaging 2016",
}