This paper addresses the problem of image registration with higher-order partial di erential equation (PDE) methods. From the study of existing a ne-linear and non-linear methods, a new framework is proposed that uniÿes common image registration methods within a generic formulation. Currently image
Diffusion tensor image up-sampling: a registration-based approach
✍ Scribed by Zhenhua Mai; Marleen Verhoye; Annemie Van der Linden; Jan Sijbers
- Publisher
- Elsevier Science
- Year
- 2010
- Tongue
- English
- Weight
- 815 KB
- Volume
- 28
- Category
- Article
- ISSN
- 0730-725X
No coin nor oath required. For personal study only.
✦ Synopsis
Diffusion weighted images (DWI), from which the corresponding diffusion tensor images (DTI) are estimated, are commonly acquired with anisotropic discretizations. Traditional methods to up-sample diffusion weighted images generally rely on scene-based interpolation and do not exploit structural information from the images. In this study, a DTI up-sampling framework is presented that incorporates the underlying anatomical shape information by means of non-rigid inter-slice registration. A strategy is proposed to reorient the interpolated tensor in order to maintain its proper orientation. Tests on phantom as well as on real data sets show that the proposed method is able to produce better results compared to scene based interpolation methods in terms of the accuracy of DWI/DTI interpolation, especially when diffusion tensor orientation is taken into account.
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