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SPHERE: SPherical Harmonic Elastic REgistration of HARDI data
Pew-Thian Yap1, Yasheng Chen, Hongyu An
1Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. ptyap@med.unc.edu
Neuroimage
|December 15, 2010
Summary
High Angular Resolution Diffusion Imaging (HARDI) registration is improved by SPherical Harmonic Elastic REgistration (SPHERE). This method hierarchically extracts orientation information for accurate brain white matter alignment.
Area of Science:
- Neuroimaging
- Medical Image Analysis
- Computational Neuroscience
Background:
- High Angular Resolution Diffusion Imaging (HARDI) offers superior brain white matter microstructure delineation compared to Diffusion Tensor Imaging (DTI).
- HARDI's complex orientation data complicates image registration, hindering accurate brain connectivity analysis.
- The optimal amount of orientation information for satisfactory HARDI alignment remains under-addressed.
Purpose of the Study:
- To develop and evaluate a novel HARDI registration algorithm for accurate structural alignment.
- To address the challenge of utilizing complex orientation information in HARDI data for improved registration.
- To systematically extract and leverage directional information from diffusion-weighted imaging for robust alignment.
Main Methods:
- Introduced SPherical Harmonic Elastic REgistration (SPHERE), a hierarchical HARDI registration algorithm.
- Employed a multi-stage approach: initial registration using Orientation Distribution Function (ODF) features, followed by refinement with Spherical Harmonic (SH) representation of increasing orders.
- Utilized a template-subject-consistent soft-correspondence matching scheme for robust alignment.
Main Results:
- SPHERE demonstrated robust and accurate alignment of HARDI data.
- The hierarchical extraction of orientation information proved effective for structural alignment.
- Experimental results showed a marked increase in accuracy compared to a state-of-the-art DTI registration algorithm.
Conclusions:
- SPHERE provides a principled and systematic method for HARDI registration.
- The algorithm's hierarchical approach effectively balances orientation information for accurate alignment.
- SPHERE offers a significant advancement in HARDI image registration accuracy for brain connectivity studies.
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