The ANTs cortical thickness processing pipeline

Nicholas J. Tustison; Brian B. Avants; Philip A. Cook; Gang Song; Sandhitsu Das; Niels van Strien; James R. Stone; James C. Gee

doi:10.1117/12.2007128

29 March 2013 The ANTs cortical thickness processing pipeline

Nicholas J. Tustison, Brian B. Avants, Philip A. Cook, Gang Song, Sandhitsu Das, Niels van Strien, James R. Stone, James C. Gee

Author Affiliations +

Proceedings Volume 8672, Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging; 86720K (2013) https://doi.org/10.1117/12.2007128
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Numerous studies have explored the relationship between cortical structure and brain development, cognitive function, and functional connectivity. The highly convoluted cortical topography makes manual measurements arduous and often impractical given the population sizes necessary for sufficient statistical power. Computational techniques have permitted large-scale studies as they provide robust and reliable localized measurements characterizing the cortex with little or no human intervention. Particularly useful to the neuroscience community are publicly available tools, such as the popular surface-based Freesurfer, which facilitate the testing and refinement of hypotheses. In this paper, we introduce the volume-based Advanced Normalization Tools (ANTs) cortical thickness automated pipeline comprising well-vetted components such as SyGN (multivariate template construction), SyN (image registration), N4 (bias correction), Atropos (n-tissue segmentation), and DiReCT (cortical thickness) all developed as part of the ANTs open science effort. Complementing the open source aspect of ANTs we demonstrate its utility using the publicly available IXI data set.

Citation Download Citation

Nicholas J. Tustison, Brian B. Avants, Philip A. Cook, Gang Song, Sandhitsu Das, Niels van Strien, James R. Stone, and James C. Gee "The ANTs cortical thickness processing pipeline", Proc. SPIE 8672, Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging, 86720K (29 March 2013); https://doi.org/10.1117/12.2007128

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