Documentation/Nightly/Extensions/MABMIS

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Introduction and Acknowledgements

Extension: MABMIS: Multi-atlas based group-wise segmentation Acknowledgments: This project was supported by NIH grant xxxxxxx. Contributor: Xiaofeng Liu, Minjeong Kim, Jim Miller, Dinggang Shen. Contact: Xiaofeng Liu, <email>xiaofeng.liu@ge.com</email>

University of North Carolina at Chapel Hill (UNC)   GE Global Research

Module Description

MABMIS is a Slicer extension that implements a multi-atlas based multi-image method for group-wise segmentation [1]. The method utilizes a novel tree-based groupwise registration method for concurrent alignment of both the atlases and the target images, and an iterative groupwise segmentation method for simultaneous consideration of segmentation information propagated from all available images, including the atlases and other newly segmented target images.

Use Cases

Input T1 Image

Brain mask as contour

Brain surface

Panels and their use

Module UI

References

• Hongjun Jia, Pew-Thian Yap, Dinggang Shen, "Iterative multi-atlas-based multi-image segmentation with tree-based registration", NeuroImage, 59:422-430, 2012.