Statistical analysis of excitation–emission matrices for laser-induced fluorescence spectroscopy

Maslov, N. A.; Papaeva, E. O.

doi:10.1134/s1063785016070257

Cited by 8 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In most cases, due to vibrational relaxation, the spectrum shape of each fluorophore does not depend on the excitation wavelength. For an optically thin sample, this means that contribution of each fluorophore is proportional to excitation and emission spectra product, making various methods of tensor PC analysis applicable [ 17 ]. However, in this case, all attempts to apply such methods failed, meaning each spectrum should be analyzed separately.…”

Section: Resultsmentioning

confidence: 99%

The Relationship between the Strength Characteristics of Cerebral Aneurysm Walls with Their Status and Laser-Induced Fluorescence Data

et al. 2021

View full text Add to dashboard Cite

Background: Cerebral aneurysms (CA) are a widespread vascular disease affecting 50 per 1000 population. The study of the influence of histological, morphological and hemodynamic factors on the status of the aneurysm has been the subject of many works. However, an accurate and generally accepted relationship has not yet been identified. Methods: In our work, the results of mechanical and spectroscopic measurements are considered. Total investigated 14 patients and 36 their samples of CA tissue. Results: The excitation–emission matrix of each specimen was evaluated, after which the strength characteristics of the samples were investigated. Conclusions: It has been shown that there is a statistically significant difference in the size of the peaks of two components, which characterizes the status of the aneurysms. In addition, a linear regression model has been built that describes the correlation of the magnitude of the ultimate strain and stress with the magnitude of the peaks of one of the components. The results of this study will serve as a basis for the non-invasive determination of the strength characteristics of the cerebral tissue aneurysms and determination of their status.

show abstract

Section: Resultsmentioning

confidence: 99%

The Relationship between the Strength Characteristics of Cerebral Aneurysm Walls with Their Status and Laser-Induced Fluorescence Data

et al. 2021

View full text Add to dashboard Cite

show abstract

“…3,4 These limitations could be overcome if each sample is provided with several correlated spectra, 5 for example by measuring the excitationemission matrix. 6 If this is not possible, for instance in the case of interacting fluorophores, some additional considerations should be used to retrieve the spectra of fluorophores by finding a suitable linear combination of PCs. All known algorithms are based on statistical analysis of PC contributions.…”

mentioning

confidence: 99%

Decomposition of multi‐component fluorescence spectra by narrow peak method based on principal component analysis

Tsibulskaya

Maslov

2021

Journal of Chemometrics

View full text Add to dashboard Cite

The main objective of multi-fluorophoric sample spectroscopy is to find the relative concentrations of individual components. If the spectra of fluorophores have broad complex shapes and significantly overlap, direct analysis is not possible.For various reasons, regression to model spectra attributed to known substances might not be easy either. Here, we describe a method of estimating the spectra of pure fluorophores in complex samples of unknown nature. This method is based on principal component analysis. Principal components themselves cannot be determined uniquely, so the method includes subsequent finding of suitable linear combinations of those principal components. Two physically reasonable assumptions were used to estimate individual fluorophore spectra: their intensities should always be non-negative and with the smallest possible spectral widths. The method's features were tested by numerical simulations using the random generated spectra of three component mixtures, experiments with optical phantom, and analysis of previously collected spectra from real tissue samples. The accuracy of the method depends on the spectral features of the samples. If spectra intersect pairwise, components could be obtained precisely. In other cases reconstructed spectra closely match the original ones, allowing them to be attributed to possible sample components. This approach makes this method convenient for various applied diagnostic tasks. It provides not only quantitative data for sample comparison, as straight principal component analysis does, but also makes data representation more demonstrative, allowing for the creation of qualitative conclusions. The method provides a unique solution dependent only on the shapes of the fluorophores' spectra. K E Y W O R D S fluorophores, laser-induced fluorescence, modeling, principal component analysis 1 | INTRODUCTION Fluorescence spectroscopy is a widely used technique in chemical and biological analysis. When dealing with multicomponent samples, its application faces certain complications. In condensed matter, collisional broadening and electrostatic interactions with surrounding molecules take place. Thus, fluorophores emit relatively broad continuous

show abstract

Adaptation of principal component analysis for continuous laser-induced fluorescence spectra decomposition. Krf excimer laser excitation examples

Maslov¹

2018

AIP Conference Proceedings

View full text Add to dashboard Cite

Statistical analysis of excitation–emission matrices for laser-induced fluorescence spectroscopy

Cited by 8 publications

References 7 publications

The Relationship between the Strength Characteristics of Cerebral Aneurysm Walls with Their Status and Laser-Induced Fluorescence Data

The Relationship between the Strength Characteristics of Cerebral Aneurysm Walls with Their Status and Laser-Induced Fluorescence Data

Decomposition of multi‐component fluorescence spectra by narrow peak method based on principal component analysis

Adaptation of principal component analysis for continuous laser-induced fluorescence spectra decomposition. Krf excimer laser excitation examples

Contact Info

Product

Resources

About