Consistent cortical reconstruction and multi-atlas brain segmentation

Yuankai Huo; Andrew J Plassard; Aaron Carass; Susan M Resnick; Dzung L Pham; Jerry L Prince; Bennett A Landman

doi:10.1016/j.neuroimage.2016.05.030

Consistent cortical reconstruction and multi-atlas brain segmentation

Neuroimage. 2016 Sep:138:197-210. doi: 10.1016/j.neuroimage.2016.05.030. Epub 2016 May 13.

Authors

Yuankai Huo¹, Andrew J Plassard², Aaron Carass³, Susan M Resnick⁴, Dzung L Pham⁵, Jerry L Prince³, Bennett A Landman⁶

Affiliations

¹ Electrical Engineering, Vanderbilt University, Nashville, TN, USA. Electronic address: yuankai.huo@vanderbilt.edu.
² Computer Science, Vanderbilt University, Nashville, TN, USA.
³ Image Analysis and Communications Laboratory, Johns Hopkins University, Baltimore, MD, USA.
⁴ Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA.
⁵ Center for Neuroscience and Regenerative Medicine, Henry Jackson Foundation, Bethesda, MD, USA.
⁶ Electrical Engineering, Vanderbilt University, Nashville, TN, USA; Computer Science, Vanderbilt University, Nashville, TN, USA; Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA.

Abstract

Whole brain segmentation and cortical surface reconstruction are two essential techniques for investigating the human brain. Spatial inconsistences, which can hinder further integrated analyses of brain structure, can result due to these two tasks typically being conducted independently of each other. FreeSurfer obtains self-consistent whole brain segmentations and cortical surfaces. It starts with subcortical segmentation, then carries out cortical surface reconstruction, and ends with cortical segmentation and labeling. However, this "segmentation to surface to parcellation" strategy has shown limitations in various cohorts such as older populations with large ventricles. 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. A modification called MaCRUISE(+) is designed to perform well when white matter lesions are present. Comparing to the benchmarks CRUISE and FreeSurfer, the surface accuracy of MaCRUISE and MaCRUISE(+) is validated using two independent datasets with expertly placed cortical landmarks. A third independent dataset with expertly delineated volumetric labels is employed to compare segmentation performance. Finally, 200MR volumetric images from an older adult sample are used to assess the robustness of MaCRUISE and FreeSurfer. The advantages of MaCRUISE are: (1) MaCRUISE constructs self-consistent voxelwise segmentations and cortical surfaces, while MaCRUISE(+) is robust to white matter pathology. (2) MaCRUISE achieves more accurate whole brain segmentations than independently conducting the multi-atlas segmentation. (3) MaCRUISE is comparable in accuracy to FreeSurfer (when FreeSurfer does not exhibit global failures) while achieving greater robustness across an older adult population. MaCRUISE has been made freely available in open source.

Keywords: Cerebral cortex; Cortical reconstruction; Magnetic resonance imaging; Multi-atlas segmentation.

Publication types

Evaluation Study
Validation Study

MeSH terms

Adult
Algorithms
Cerebral Cortex / anatomy & histology*
Cerebral Cortex / diagnostic imaging*
Female
Humans
Image Enhancement / methods*
Image Interpretation, Computer-Assisted / methods*
Magnetic Resonance Imaging / methods*
Male
Middle Aged
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity
Subtraction Technique*

Abstract

Publication types

MeSH terms

Grants and funding