Iranian Journal of Medical Physics

Iranian Journal of Medical Physics

Spectral Separation of Quantum Dots within Tissue Equivalent Phantom Using Linear Unmixing Methods in Multispectral Fluorescence Reflectance Imaging

Document Type : Original Paper

Authors
Ebrahim Najafzadeh 1
Marjaneh Hejazi 2
Alireza Ahmadian 3
Hanieh Mohamadreza 4
1 Ardabil University of Medical Sciences, Ardabil, Iran
2 Medical Physics and Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
3 Medical Physics and Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
4 Bio Optical Imaging Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.
10.22038/ijmp.2012.149
Abstract
Introduction
Non-invasive Fluorescent Reflectance Imaging (FRI) is used for accessing physiological and molecular processes in biological media. The aim of this article is to separate the overlapping emission spectra of quantum dots within tissue-equivalent phantom using SVD, Jacobi SVD, and NMF methods in the FRI mode.
Materials and Methods
In this article, a tissue-like phantom and an optical setup in reflectance mode were developed. The algorithm of multispectral imaging method was then written in Matlab environment. The setup included the diode-pumped solid-state lasers at 479 nm, 533 nm, and 798 nm, achromatic telescopic, mirror, high pass and low pass filters, and EMCCD camera. The FRI images were acquired by a CCD camera using band pass filter centered at 600 nm and high pass max at 615 nm for the first region and high pass filter max at 810 nm for the second region. The SVD and Jacobi SVD algorithms were written in Matlab environment and compared with a Non-negative Matrix Factorization (NMF) and applied to the obtained images.
Results
PSNR, SNR, CNR of SVD, and NMF methods were obtained as 39 dB, 30.1 dB, and 0.7 dB, respectively. The results showed that the difference of Jacobi SVD PSNR with PSNR of NMF and modified NMF algorithm was significant (p<0.0001). The statistical results showed that the Jacobi SVD was more accurate than modified NMF.
Conclusion
In this study, the Jacobi SVD was introduced as a powerful method for obtaining the unmixed FRI images. An experimental evaluation of the algorithm will be done in the near future.
Keywords
Fluorescent Reflectance Imaging
Jacobi SVD
Non-Negative Matrix Factorization
Multispectral Imaging
SVD
Subjects
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Iranian Journal of Medical Physics
Volume 9, Issue 3 - Serial Number 3
September and October 2012
Pages 177-182

  • Receive Date 02 October 2011
  • Revise Date 23 January 2013
  • Accept Date 15 March 2012