Documentation/Nightly/Extensions/PBNRR

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Introduction and Acknowledgements

Extension: Physics-Based Non-Rigid Registration (PBNRR) Acknowledgments: This work is funded mainly by the ARRA funds for the ITK-v4 implementation with grant number:NLMA2D2201000586P. In addition, this work is supported in part by NSFgrants:CCF-1139864, CCF-1136538, and CSI-1136536 and by the John Simon Guggenheim Foundation and the Richard T.Cheng Endowment. Author: Fotis Drakopoulos Contributors: Fotis Drakopoulos (CRTC), Yixun Liu (CRTC), Andriy Kot (CRTC), Andrey Fedorov (SPL B&W Harvard), Olivier Clatz (Asclepios INRIA), Nikos Chrisochoides (CRTC) Contact: Nikos Chrisochoides, <email>npchris@gmail.com</email> Website: https://crtc.cs.odu.edu/joomla/ License: BSD

Center for Real-time Computing

Module Description

The module Non-Rigid Registers a moving to a fixed MRI. It uses a linear homogeneous bio-mechanical model to compute a dense deformation field that defines a transformation for every point in the fixed image to the moving image. The method includes three components (Feature Point Selection, Block Matching and Finite Element Solver) combine together to provide a user-friendly interface.

Use Cases

Case1 input; top left: moving image, top right: mesh, bottom left: fixed image, bottom right: mask image.

Case2 input; top left: moving image, top right: mesh, bottom left: fixed image, bottom right: mask image.

Panels and their use

Module UI

References

• Xiaodong Tao, Ming-ching Chang, “A Skull Stripping Method Using Deformable Surface and Tissue Classification”, SPIE Medical Imaging, San Diego, CA, 2010.
• Ming-ching Chang, Xiaodong Tao “Subvoxel Segmentation and Representation of Brain Cortex Using Fuzzy Clustering and Gradient Vector Diffusion”, SPIE Medical Imaging, San Diego, CA, 2010.