Information-Theoretic Algorithms for Diffusion Tensor Imaging

author: Baba C. Vemuri, University of Florida
published: Dec. 5, 2008,   recorded: November 2008,   views: 12613


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Concepts from Information Theory have been used quite widely in Image Processing, Computer Vision and Medical Image Analysis for several decades now. Most widely used concepts are that of KL-divergence, minimum description length (MDL), etc. These concepts have been popularly employed for image registration, segmentation, classification etc. In this chapter we review several methods, mostly developed by our group at the Center for Vision, Graphics & Medical Imaging in the University of Florida, that glean concepts from Information Theory and apply them to achieve analysis of Diffusion-Weighted Magnetic Resonance (DW-MRI) data. This relatively new MRI modality allows one to non-invasively infer axonal connectivity patterns in the central nervous system. The focus of this chapter is to review automated image analysis techniques that allow us to automatically segment the region of interest in the DWMRI image wherein one might want to track the axonal pathways and also methods to reconstruct complex local tissue geometries containing axonal fiber crossings. Implementation results illustrating the algorithm application to real DW-MRI data sets are depicted to demonstrate the effectiveness of the methods reviewed.

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Reviews and comments:

Comment1 Thanos, November 26, 2018 at 7:04 a.m.:

There are the nice video here it is the very interesting you can access here the all internet windows setting and seen the out look way on the browser easily thanks.

Comment2 IMo for pc, October 12, 2019 at 11:57 a.m.:

DTI is a sensitive probe of cellular structure that works by measuring the diffusion of water molecules. ... This example compares the diffusion measured parallel and perpendicular to the axons in a white matter fiber tract. The diffusion tensor (DT) describes the diffusion of water molecules using a Gaussian model.
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