Multispectral Imaging in Combination with Multivariate Analysis Discriminates Selenite Induced Cataractous Lenses from Healthy Lenses of Sprague-Dawley Rats

Adueming, Peter Osei-Wusu; Eghan, Moses Jojo; Anderson, Benjamin; Kyei, Samuel; Opoku-Ansah, Jerry; Amuah, Charles Lloyd Yeboah; Sackey, Samuel Sonko; Buah-Bassuah, Paul K

doi:10.4236/ojbiphy.2017.73011

Cited by 4 publications

(1 citation statement)

References 27 publications

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“…e FLDA of the pixel intensities data follows a procedure described by Adueming et al [51]. Allocation rule obtained from the FLDA function for the pixel intensities data of the u-RBCs and the i-RBCs) is given as…”

Section: Linear Discriminant Analysismentioning

confidence: 99%

Optical Identification of Plasmodium falciparum Malarial Byproduct for Parasite Density Estimation

Opoku-Ansah

Eghan

Anderson

et al. 2019

International Journal of Optics

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Plasmodium falciparum (P. falciparum) malarial degree of infection, termed as parasite density (PD), estimation is vital for point-of-care diagnosis and treatment of the disease. In this work, we present application of optical techniques: optical absorption and multispectral imaging for P. falciparum malarial byproduct (hemozoin) detection in human‐infected blood samples to estimate PD. The blood samples were collected from volunteers who were tested positive for P. falciparum infections (i-blood), and after treatment, another set of blood samples (u-blood) were also taken. The i-blood samples were grouped based on PD (+, ++, +++, and ++++). Optical densities (ODs) of u-blood samples and i-blood samples at blood absorption bands of 405 nm, 541 nm, and 577 nm showed different optical absorption characteristics. Empirical computation of ratio of the ODs for the blood absorption bands revealed reduction in the ODs with increasing PD. Multispectral images containing uninfected red blood cells (u-RBCs) and P. falciparum‐infected red blood cells (i-RBCs) on unstained blood smear slides exhibited spectrally determined decrease in both reflected and scattered pixel intensities and increase in transmitted pixel intensities with increasing PD. We further propose a linear classification model based on Fisher’s approach using reflected, scattered, and transmitted pixel intensities for easy and inexpensive estimation of PD as an alternative to manual estimation of PD, currently, the widely used technique. Application of the optical techniques and the proposed linear classification model are therefore recommended for improved malaria diagnosis and therapy.

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Section: Linear Discriminant Analysismentioning

confidence: 99%

Optical Identification of Plasmodium falciparum Malarial Byproduct for Parasite Density Estimation

Opoku-Ansah

Eghan

Anderson

et al. 2019

International Journal of Optics

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View full text Add to dashboard Cite

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Laser-induced autofluorescence assisted by multivariate techniques discriminates a cataractous lens from healthy lens tissues of Sprague–Dawley rats

et al. 2020

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Laser-induced autofluorescence (LIAF), combined with multivariate techniques, has been used to discriminate a cataractous lens from healthy lens tissues. In this study, 405 nm and 445 nm were used as excitation sources to induce the autofluorescence. Results show higher autofluorescence intensity in cataractous lens tissues than in healthy ones. Cataractous lens tissues show a red shift of 0.9 nm and 1.2 nm at 405 nm and 445 nm excitations, respectively. Using principal component analysis (PCA), three principal components (PCs) gave more than 99% variability for both 405 nm and 445 nm excitation sources. Based on the three PCs, Fisher’s linear discriminant model was developed. An accuracy of 100% was obtained in classifying the lens tissues using Fisher’s linear discriminant analysis (FLDA). The LIAF technique assisted by PCA and FLDA may be used for objective discrimination of cataractous lens from healthy lens tissues of Sprague–Dawley rats.

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Laser-induced fluorescence combined with multivariate techniques identifies the geographical origin of antimalarial herbal plants

et al. 2020

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Laser-induced fluorescence (LIF) combined with multivariate techniques has been used in identifying antimalarial herbal plants (AMHPs) based on their geographical origin. The AMHP samples were collected from four geographical origins (Abrafo, Jukwa, Nfuom, and Akotokyere) in the Cape Coast Metropolis, Ghana. LIF spectra data were recorded from the AMHP samples. Utilizing multivariate techniques, a training set for the first two principal components of the AMHP spectra data was modeled through the use of K-nearest neighbor (KNN), support vector nachine (SVM), and linear discriminant analysis (LDA) methods. The SVM and KNN methods performed best with 100% success for the prediction data, while the LDA had a 99% success rate. The KNN and SVM methods are recommended for the identification of AMHPs based on their geographical origins. Deconvoluted peaks from the LIF spectra of all the AMHP samples revealed compounds such as quercetin and berberine as being present in all the AMHP samples.

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Multispectral Imaging in Combination with Multivariate Analysis Discriminates Selenite Induced Cataractous Lenses from Healthy Lenses of Sprague-Dawley Rats

Cited by 4 publications

References 27 publications

Optical Identification of Plasmodium falciparum Malarial Byproduct for Parasite Density Estimation

Optical Identification of Plasmodium falciparum Malarial Byproduct for Parasite Density Estimation

Laser-induced autofluorescence assisted by multivariate techniques discriminates a cataractous lens from healthy lens tissues of Sprague–Dawley rats

Laser-induced fluorescence combined with multivariate techniques identifies the geographical origin of antimalarial herbal plants

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