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Abstract Details
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Activity Number:
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634
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Type:
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Contributed
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Date/Time:
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Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #301942 |
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Title:
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Statistical Analysis of Raman-Spectroscopic Images, with Applications to Clinical Assessment of Bone Structure Parameters
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Author(s):
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Ruth Cassidy*+
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Companies:
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University of Michigan
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Address:
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439 West Hall, Ann Arbor, MI, 48109, United States
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Keywords:
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imaging ;
Raman-spectroscopy ;
high-dimensional ;
modeling ;
classification
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Abstract:
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Raman-spectroscopic imaging is a non-invasive technique used to study the chemical composition of a given material or living system. Images can be used for either pixel- or subject- level prediction. Analysis of Raman-spectroscopic images can be challenging due to the high-dimensional nature of spectra and the large amount of noise. Existing dimension reduction methods for Raman spectra often assume an idealized linear superposition model, which may be inadequate in practice. Moreover, many methods ignore the spatial structure and/or the functional nature of the data. We propose a method that models the salient features of spectral peaks while accounting for spatial information via the use of regularization. The method is demonstrated on an application to bone tissue classification.
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Authors who are presenting talks have a * after their name.
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