NDLI: On Characterizing and Analyzing Diffusion Tensor Images by Learning their Underlying Manifold Structure

Content Provider	IEEE Xplore Digital Library
Author	Khurd, P. Verma, R. Davatzikos, C.
Copyright Year	2006
Description	Author affiliation: University of Pennsylvania, USA (Khurd, P.)
Abstract	The growing importance of diffusion tensor imaging (DTI) in studying the white matter architecture in normal and pathologic states necessitates the development of tools for comprehensive analysis of diffusion tensor data. Operations such as multivariate statistical analysis and hypothesis testing, interpolation and filtering, must now be performed on tensor data, and must overcome challenges introduced by the non-linearity and high dimensionality of the tensors. In this paper, we present a novel approach to performing these computations by modeling the underlying manifold structure of the tensors, using a combination of two manifold learning techniques, isometric mapping (ISOMAP) and local tangent space alignment (LTSA). While ISOMAP identifies the dimensionality of the manifold of the tensors and embeds the tensors into a linear space, facilitating statistical computations therein, operations like interpolation and filtering, integral to the process of normalization, require the reconstruction of the tensor in the tensor domain. To obtain this reverse mapping from the linear space to the tensor domain, i.e. to the domain of the original tensor data, we use LTSA. The modeling of the underlying manifold structure renders our approach better applicable to tensor data than existing methods that may not always be able to capture the non-linearity present in the tensors under consideration. In various simulations with known ground truth, we demonstrate the effectiveness of our framework based on ISOMAP and LTSA in performing a comprehensive analysis of DTI data.
Starting Page	61
Ending Page	61
File Size	810620
Page Count	1
File Format	PDF
ISBN	0769526462
DOI	10.1109/CVPRW.2006.148
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance evaluation Interpolation Embedded computing Image analysis Tensile stress Filtering Statistical analysis Computational modeling Diffusion tensor imaging Testing
Content Type	Text
Resource Type	Article

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