Title of article :
Spectral Separation of Quantum Dots within Tissue Equivalent Phantom Using Linear Unmixing Methods in Multispectral Fluorescence Reflectance Imaging
Author/Authors :
Najafzadeh, Ebrahim ardabil university of medical sciences, ايران , Hejazi, Marjaneh tehran university of medical sciences tums - School of Medicine - Medical Physics and Biomedical Engineering Department, تهران, ايران , Hejazi, Marjaneh tehran university of medical sciences tums - Research Center for Molecular and Cellular Imaging - Bio Optical Imaging Group, تهران, ايران , Ahmadian, Alireza tehran university of medical sciences tums - School of Medicine - Medical Physics and Biomedical Engineering Department, تهران, ايران , Ahmadian, Alireza tehran university of medical sciences tums - Research Center in Biomedical Research Center in Biomedical Technology and Robotics - Medical Imaging System Group, تهران, ايران , Mohamadreza, Hanieh tehran university of medical sciences tums - Research Center for Molecular and Cellular Imaging - Bio Optical Imaging Group, تهران, ايران
From page :
177
To page :
182
Abstract :
IntroductionNon-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 MethodsIn 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.ResultsPSNR, 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.ConclusionIn 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
Journal title :
Iranian Journal of Medical Physics (IJMP)
Journal title :
Iranian Journal of Medical Physics (IJMP)
Record number :
2570836
Link To Document :
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