Multivariate curve resolution for hyperspectral image analysis: applications to microarray technology

2003 ◽  
Author(s):  
David M. Haaland ◽  
Jerilyn A. Timlin ◽  
Michael B. Sinclair ◽  
Mark H. Van Benthem ◽  
M. Juanita Martinez ◽  
...  
Keyword(s):  
Image Analysis ◽  
Hyperspectral Image ◽  
Multivariate Curve Resolution ◽  
Microarray Technology ◽  
Curve Resolution ◽  
Hyperspectral Image Analysis

Application of Multivariate Curve Resolution for Analysis of FT-IR Microspectroscopic Images of in Situ Plant Tissue

2003 ◽  
Vol 57 (2) ◽  
pp. 124-131 ◽  
Author(s):  
Boiana O. Budevska ◽  
Stephen T. Sum ◽  
Todd J. Jones
Keyword(s):  
Prior Information ◽  
Hyperspectral Image ◽  
Univariate Analysis ◽  
Hyperspectral Images ◽  
Multivariate Curve Resolution ◽  
Curve Resolution ◽  
Hyperspectral Image Analysis ◽  
Ft Ir ◽  
Components Analysis

The chemometric techniques of multivariate curve resolution (MCR) are aimed at extracting the spectra and concentrations of individual components present in mixtures using a minimum set of initial assumptions. We present results from the application of alternating least squares (ALS) based MCR to the analysis of hyperspectral images of in situ biological material. The spectra of individual pure components were mathematically extracted and then identified by searching the spectra against a commercial library. No prior information about the chemical composition of the material was used in the data analysis. The spectra recovered by ALS-MCR analysis of an FT-IR microspectroscopic image of an 8-μm-cornkernel section matched very well the spectra of the corn storage protein, zein, and starch. Through the application of MCR, we were able to show the presence of a second spectrally different protein, which could not be easily seen using univariate analysis. These results demonstrate the value of multivariate curve resolution techniques for the analysis of biological tissue. The value of principal components analysis (PCA) for hyperspectral image analysis is also discussed.

scholarly journals Trends in Deep Learning for Medical Hyperspectral Image Analysis

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Uzair Khan ◽  
Sidike Paheding ◽  
Colin Elkin ◽  
Vijay Devabhaktuni
Keyword(s):  
Image Analysis ◽  
Deep Learning ◽  
Hyperspectral Image ◽  
Hyperspectral Image Analysis

Weighting hyperspectral image data for improved multivariate curve resolution results

2008 ◽  
Vol 22 (9) ◽  
pp. 482-490 ◽  
Author(s):  
Howland D. T. Jones ◽  
David M. Haaland ◽  
Michael B. Sinclair ◽  
David K. Melgaard ◽  
Mark H. Van Benthem ◽  
...  
Keyword(s):  
Hyperspectral Image ◽  
Image Data ◽  
Multivariate Curve Resolution ◽  
Curve Resolution ◽  
Hyperspectral Image Data

An update on the MATLAB hyperspectral image analysis toolbox

2005 ◽  
Author(s):  
Samuel Rosario-Torres ◽  
Emmanuel Arzuaga-Cruz ◽  
Miguel Velez-Reyes ◽  
Luis O. Jimenez-Rodriguez
Keyword(s):  
Image Analysis ◽  
Hyperspectral Image ◽  
Hyperspectral Image Analysis
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