Mueller matrix imaging polarimetry technique for dengue fever detection

Le, Huy-Mai; Le, Thanh-Hai; Phan, Quoc Hung; Pham, Thi-Thu-Hien

doi:10.1016/j.optcom.2021.127420

Cited by 17 publications

(7 citation statements)

References 32 publications

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“…It is noted that these results show a good quantitative agreement with those obtained from Ref. 33 and are consistent with the results reported in Ref. 45 .…”

Section: Resultssupporting

confidence: 92%

“…Furthermore, the system was also employed by the present group for dengue detection. 33 Thus, the feasibility of the measurement for extracting the Mueller matrix of anisotropic turbid media is confirmed. When performing the experiments, HBV samples were stored in a 1.3 mm-thickness quartz cuvette (Thorlabs Inc., CV10Q35F).…”

Section: Methodsmentioning

confidence: 77%

“…In performing the measurement process, the incident angle was set to 60 deg to prevent the reflection of the incident light from the sample surface and to obtain a good polarization image. 33 , 42 Moreover, the polarizers (P1, P2) and quarter waveplates (QW1, QW2) in the PSG and PSA were mounted on rotators (Sigma Koki Co., SGSP-60YAW-0B) to generate the 36 polarization states required to construct the Mueller matrix of each sample. In the PSG, the linear polarization states (0 deg, 45 deg, 90 deg, and 135 deg) were generated simply by rotating the polarizer (P1).…”

Section: Methodsmentioning

confidence: 99%

“…In a previous study, the present group proposed a polarization technique for characterizing the optical properties of turbid media. 31 , 32 Recently, the same group developed a polarization technique for dengue virus detection 33 and skin cancer detection using deep learning techniques based on polarization properties. 34 , 35 In this study, a combination of MMIP and AI classification framework was utilized to perform HBV detection in human blood serum samples in the reflectance configuration.…”

Section: Introductionmentioning

confidence: 99%

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Combined Mueller matrix imaging and artificial intelligence classification framework for Hepatitis B detection

et al. 2022

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. Significance: The combination of polarized imaging with artificial intelligence (AI) technology has provided a powerful tool for performing an objective and precise diagnosis in medicine. Aim: An approach is proposed for the detection of hepatitis B (HB) virus using a combined Mueller matrix imaging technique and deep learning method. Approach: In the proposed approach, Mueller matrix imaging polarimetry is applied to obtain Mueller matrix images of 138 HBsAg-containing (positive) serum samples and 136 HBsAg-free (negative) serum samples. The kernel estimation density results show that, of the 16 Mueller matrix elements, elements and provide the best discriminatory power between the positive and negative samples. Results: As a result, and are taken as the inputs to five different deep learning models: Xception, VGG16, VGG19, ResNet 50, and ResNet150. It is shown that the optimal classification accuracy (94.5%) is obtained using the VGG19 model with element as the input. Conclusions: Overall, the results confirm that the proposed hybrid Mueller matrix imaging and AI framework provides a simple and effective approach for HB virus detection.

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“…It is noted that these results show a good quantitative agreement with those obtained from Ref. 33 and are consistent with the results reported in Ref. 45 .…”

Section: Resultssupporting

confidence: 92%

Section: Methodsmentioning

confidence: 77%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Combined Mueller matrix imaging and artificial intelligence classification framework for Hepatitis B detection

et al. 2022

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“…In fact, Mueller polarimetry is used in astrobiology, in the search for biological molecules (biosignatures) outside the Earth [42] , [43] , [44] . Recent works highlight the potential of the analysis of the vectorial properties of light beams interacting with samples for many biomedical applications [45] , including the detection of viruses [ 46 , 47 ]. However, further studies in this field are required to clarify whether said detection and discrimination in complex biological media (e.g., blood) relate to specific elements (e.g., viruses), or to the effects that they produce in tissues or structures.…”

Section: Introductionmentioning

confidence: 99%

Polarimetric imaging for the detection of synthetic models of SARS-CoV-2: A proof of concept

Gómez-González¹,

Muñoz²,

Gómez-Martín³

et al. 2023

Journal of Quantitative Spectroscopy and Radiative Transfer

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Wide‐field Mueller matrix polarimetry for spectral characterization of basic biological tissues: Muscle, fat, connective tissue, and skin

Pardo,

Bian,

Gomis‐Brescó

et al. 2023

Journal of Biophotonics

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This study investigates the polarimetric properties of skin, skeletal muscle, connective tissue, and fat using Mueller matrix imaging. It aims to compare the polarimetric characteristics of these tissues and explore how they evolve with wavelength. Additionally, the temporal evolution of certain tissues during meat aging is studied, providing insights into the dynamic behavior of polarimetric properties over time. The research employs back‐scattering configuration and the differential decomposition analysis method of Mueller matrix images. Both in‐vivo and ex‐vivo experiments were conducted using a consistent instrument setup to ensure reliable analysis. The results reveal wavelength‐dependent variations in tissue properties, including an increase in depolarization with wavelength. Significant differences in the polarimetric characteristics of meat tissues, particularly for skeletal muscle, are observed. Over a 24‐hour period, intensity, diattenuation, and retardation experience alterations, being the decreased retardation in skeletal muscle and the increased retardation in fat the most notable ones.This article is protected by copyright. All rights reserved.

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Mueller matrix imaging polarimetry technique for dengue fever detection

Cited by 17 publications

References 32 publications

Combined Mueller matrix imaging and artificial intelligence classification framework for Hepatitis B detection

Combined Mueller matrix imaging and artificial intelligence classification framework for Hepatitis B detection

Polarimetric imaging for the detection of synthetic models of SARS-CoV-2: A proof of concept

Wide‐field Mueller matrix polarimetry for spectral characterization of basic biological tissues: Muscle, fat, connective tissue, and skin

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