GLIRT (Groupwise and Longitudinal Image Registration Toolbox)

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GLIRT (Groupwise and Longitudinal Image Registration Toolbox) provides solutions for both groupwise registration and longitudinal registration, which are the necessary steps for many brain-related applications. Specifically, groupwise registration is important for unbiased analysis of a large set of MR brain images. Therefore, in this software package, we have included two of our recently-developed groupwise registration algorithms: 1) Improved unbiased groupwise registration guided with the sharp group-mean image, and 2) Hierarchical feature-based groupwise registration with implicit template (Called as Groupwise-HAMMER for short). On the other hand, in this software package, we also included our recently-developed groupwise longitudinal registration algorithm that aligns not only the longitudinal image sequence for each subject, but also align all longitudinal image sequences of all subjects to the common space simultaneously.

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Related Softwares

ABSORB

HAMMER-SUITE

HAMMER ITK Implementation


Details for the three methods included in this software package can be found in the following three papers:
• Improved unbiased groupwise registration guided by sharp group-mean image:
1. Wu, G., Jia, H., Wang, Q., Shen, D.: Groupwise Registration with Sharp Mean. MICCAI 2010, Beijing (2010)
2. Wu, G., Jia, H., Wang, Q., Shen, D.: SharpMean: Groupwise Registration Guilded by Sharp Mean Image and Tree-based Registration. NeuroImage, 56(4): 1968-1981, June. 2011.


• Hierarchical feature-based groupwise registration with implicit template:
1. Wu, G., Wang, Q., Jia, H., Shen, D.: Groupwise Registration by Hierarchical Anatomical Correspondence Detection. MICCAI 2010, Beijing (2010)
2. Wu, G., Wang, Q., Jia, H., Shen, D.: Feature-based Groupwise Registration by Hierarchical Anatomical Correspondence Detection. Human Brain Mapping, vol. 33, pp. 253-271, 2012.


• Groupwise longitudinal registration:
1. Wu, G., Wang, Q., Jia, H., Shen, D.: Registration of Longitudinal Image Sequences with Implicit Template and Spatial-Temporal Heuristics. MICCAI 2010, Beijing (2010)

2. Guorong Wu, Qian Wang, Dinggang Shen, “Registration of Longitudinal Image Sequences with Implicit Template and Spatial-Temporal Heuristics”, NeuroImage, vol. 59(1), pp. 404-412, 2012.


If you have any question in using GLIRT, please send email to Dr. Guorong Wu or leave the message at GLIRT forums. In addition, this software package was developed in the IDEA group at UNC-Chapel Hill. For more information, please visit our lab at http://bric.unc.edu/ideagroup.