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Erschienen in:
2005 | OriginalPaper | Buchkapitel
3D Curve Inference for Diffusion MRI Regularization
verfasst von : Peter Savadjiev, Jennifer S. W. Campbell, G. Bruce Pike, Kaleem Siddiqi
Erschienen in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005
Verlag: Springer Berlin Heidelberg
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We develop a differential geometric framework for regularizing diffusion MRI data. The key idea is to model white matter fibers as 3D space curves and to then extend Parent and Zucker’s 2D curve inference approach [8] by using a notion of
co-helicity
to indicate compatibility between fibre orientation estimates at each voxel with those in a local neighborhood. We argue that this provides several advantages over earlier regularization methods. We validate the approach quantitatively on a biological phantom and on synthetic data, and qualitatively on data acquired
in vivo
from a human brain.