Paper
11 April 2008 Linear spectral unmixing approaches to magnetic resonance image analysis
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Abstract
Since Magnetic Resonance (MR) images can be considered as multispectral images where each spectral band image is acquired by a particular pulse sequence, this paper investigates an application of a technique that is widely used in multispectral image processing, referred to as Linear Spectral Unmixing (LSU), in MR image analysis where two types of LSU, unconstrained LSU and constrained LSU are considered. Due to a limited number of MR images acquired by MR sequences, the ability of the LSU cannot be fully explored and utilized. In order to mitigate this dilemma, a band expansion process is introduced to expand an original set of MR images to an augmented set of multsipectral images by including additional spectral band images that can be generated from the original MR images using a set of nonlinear functions. In order to demonstrate the utility of the LSU in MR image analysis, two sets of MR images, synthetic MR images available on website and real MR images, are used for experiments. Experimental results show that the LSU can be a very effective technique in quantifying MR substances to calculate their partial volumes for further MR image analysis.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark Englin Wong and Chein-I Chang "Linear spectral unmixing approaches to magnetic resonance image analysis", Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69660K (11 April 2008); https://doi.org/10.1117/12.782220
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Cited by 1 scholarly publication.
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KEYWORDS
Magnetic resonance imaging

Brain

Signal to noise ratio

Neuroimaging

Statistical analysis

Image processing

Image analysis

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