Polarized Light-Based Cancer Cell Detection Techniques: A Review

Tukimin, Siti Nurainie; Karman, Salmah; Ahmad, Mohd Yazed; Zaman, Wan Safwani Wan Kamarul

doi:10.1109/jsen.2019.2924535

Cited by 20 publications

(14 citation statements)

References 226 publications

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“…Kushwaha and Patel proposed a weighted median filter; this method has a good denoising effect on impulse noise and small speckle noise, for example, ceramic surface image, but it is not ideal for denoising the image with a large scatter size like ceramic surface image [10]. Ghannadi et al [11] proposed a new full variational block matching ceramic surface image noise reduction algorithm by combining the full variational algorithm with the 3D block matching image noise reduction algorithm [12]. Chen et al proposed an image correlation noise reduction algorithm, which first uses the target characteristics to reject the stationary target and then further filters the random noise by using the persistence of target motion and the spatial location correlation of target echoes in consecutive multiframe images [13].…”

Section: Related Workmentioning

confidence: 99%

“…Using the threshold rule means that if white noise satisfying the standard normal distribution is added to the signal, the noise has a high probability of being lower than N, so it is usually used as the threshold, as in Equation (12), where β is the standard deviation of the noise and N is the length of the signal. It can be seen that the magnitude of the threshold value is positively correlated with the length of the signal.…”

Section: Wavelet Analysis-based Texture Analysis Of Ceramic Surface Imagesmentioning

confidence: 99%

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Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images

Liu

Zhou

Yang

2021

Advances in Mathematical Physics

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This paper is conducted to explore a new characterization method as a supplement to the traditional roughness characterization. The main research includes the extraction and evaluation of damage features of ceramic surface morphology by applying wavelet methods, the extraction of damage features in surface contours by using wavelet analysis, and the quantitative evaluation of damage degree by using damage rate and damage mean spacing. By comparing various fractal dimension calculation methods, a fractal dimension method suitable for calculating the ceramic surface was selected, and the fractal method was used to describe the ceramic surface topography as a whole. By comparing different methods of calculating the fractal dimension and further verifying them with the measured three-dimensional morphology, it is found that the vibrational method is more suitable for calculating the fractal dimension of ceramic surface, and its calculation accuracy is investigated, and the results show that the method is a reliable one. Based on the fractal theory, a mathematical model of surface wear and surface sealing was established. Further study of the model shows that the surface with a large fractal dimension has a good sealing effect; the surface corresponding to the best fractal dimension is the most resistant to wear. The fractal method can characterize the complexity of the surface profile as a whole. The wavelet method can describe the ceramic surface profile from a local perspective, and the combination of the two methods can characterize the ceramic surface well. Finally, the experimental device of the ceramic surface defect detection system is constructed, and the joint debugging of hardware and software is completed. Under different light source intensities, ceramic image samples are collected, and the accuracy detection experiments of sample defective edges are conducted, and the results show that the light source has a small impact on the accuracy of ceramic defective edge detection. The results show that the light source has more influence on the accuracy of scratch detection. The results show that the system constructed in this thesis has good applicability for different ceramic sample detection.

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Section: Related Workmentioning

confidence: 99%

Section: Wavelet Analysis-based Texture Analysis Of Ceramic Surface Imagesmentioning

confidence: 99%

Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images

Liu

Zhou

Yang

2021

Advances in Mathematical Physics

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“…Revealing the mechanisms of interaction between photons and complex biological tissues is one of the major goals of biomedical optics research, which is essential for therapeutic and diagnostic applications [1–9]. Polarization is one of the fundamental properties of light and a promising method that has been applied to many fields, including biological tissues [3, 10–14]. Most biological tissues are structurally anisotropic turbid media containing fibrous components, such as axons, capillary vessels, collagen fibers or myofibrils [15].…”

Section: Introductionmentioning

confidence: 99%

Study of the spatial scale stability of Mueller matrix parameters for textural characterization of biological tissues

Chen

Chu

Tang

et al. 2021

Journal of Biophotonics

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Mueller matrix imaging polarimetry (MMIP) is a promising technique for the textural characterization of biological tissue structures. To reveal the influence of imaging magnification on the robustness of Mueller matrix parameters (MMPs), the spatial scale stability of MMPs was studied. We established a new MMIP detector and derived the mathematical model of the spatial scale stability of MMPs. The biological tissues with well‐defined structural components were imaged under different magnifications. Then, we compared and analyzed the textural features of the MMPs in the resulting images. The experimental results match the predictions of the mathematical model in these aspects: (a) magnification exhibits a strong nonlinear effect on the textural contrasts of MMPs images; (b) higher magnification does not necessarily lead to superior contrast for textural characterization; and (c) for different biological tissues, MMPs contrasts can be optimized differently, with some showing superior results. This study provides a reference for the experimental design and operation of the MMIP technique and is helpful for improving the characterization ability of MMPs.

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“…With the expansion of the demand for remote sensing information, polarized remote sensing information can solve problems that cannot be solved in the traditional remote sensing field, and effectively improve the accuracy of feature recognition. Thus, it has become a valuable tool in many applications, including cloud and atmospheric aerosol detection, geological exploration, soil analyses, and medical diagnoses [ 2 , 3 , 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

“…At different spatial scales, the inversion or classification accuracy varies significantly. This affects judgements concerning the impact of the classification of terrain, spring phenology detections, the estimation of the fire range, and the inversion of vegetation evaporation [ 4 , 5 , 6 , 7 , 8 , 9 ]. Additionally, the phenomena and summary rules on a specific scale may be valid on another scale, but it is not entirely applicable.…”

Section: Introductionmentioning

confidence: 99%

Spatial Scale Effect of a Typical Polarized Remote Sensor on Detecting Ground Objects

Zhang

Sun

Qiu

et al. 2021

Sensors

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For polarized remote sensors, the polarization images of ground objects acquired at different spatial scales will be different due to the spatial heterogeneity of the ground object targets and the limitation of imaging resolution. In this paper, the quantitative inversion problem of a typical polarized remote sensor at different spatial scales was studied. Firstly, the surface roughness of coatings was inversed based on the polarized bidirectional reflectance distribution function (pBRDF) model according to their polarization images at different distances. A linear-mixed pixel model was used to make a preliminary correction of the spatial scale effect. Secondly, the super-resolution image reconstruction of the polarization imager was realized based on the projection onto convex sets (POCS) method. Then, images with different resolutions at a fixed distance were obtained by utilizing this super-resolution image reconstruction method and the optimal spatial scale under the scene can be acquired by using information entropy as an evaluation indicator. Finally, the experimental results showed that the roughness inversion of coatings has the highest accuracy in the optimal spatial scale. It has been proved that our proposed method can provide a reliable way to reduce the spatial effect of the polarized remote sensor and to improve the inversion accuracy.

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Polarized Light-Based Cancer Cell Detection Techniques: A Review

Cited by 20 publications

References 226 publications

Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images

Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images

Study of the spatial scale stability of Mueller matrix parameters for textural characterization of biological tissues

Spatial Scale Effect of a Typical Polarized Remote Sensor on Detecting Ground Objects

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