Tensor Field Regularization Using Normalized Convolution

Topics:
Healthcare Services
Tags:
Productivity,
Springer Science+Business Media,
Technique
Source:
Springer Science+Business Media

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Overview: This paper presents a filtering technique for regularizing tensor fields. It uses a nonlinear filtering technique termed normalized convolution, a general method for filtering missing and uncertain data. In the present work we extend the signal certainty function to depend on locally derived certainty information in addition to the priory voxel certainty. This results in reduced blurring between regions of different signal characteristics, and increased robustness to outliers. A driving application for this work has been filtering of data from Diffusion Tensor MRI.

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Format: PDF | Size: 792KB | Date: Apr 2004 | Pages: 9

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