Comparison of different calibration methods for Mueller matrix microscopy of cells

Meng, Ruoyu; Chen, Zhenhua; Wang, Xingjian; Liu, Yudi; He, Honghui; Ma, Hui

doi:10.1364/ao.411625

Cited by 15 publications

(6 citation statements)

References 31 publications

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“…It is capable of taking a Mueller matrix image in about 3 min with less than 0.02 average root mean square error (RMSE) using standard samples including air, linear polarizer, and waveplate. Details for optimization and calibration of the microscope can be found in previous studies 10 , 23 – 25 . A small number of samples were imaged by an upgraded MMM 26 whose polarization state analyzer and 2D detector were replaced by two 2048 × 2448 pixels 16-bit division of focal plane (DoFP) polarimeters (PHX050S-PC, Lucid Vision Labs Inc., Canada).…”

Section: Methodsmentioning

confidence: 99%

Unsupervised learning of pixel clustering in Mueller matrix images for mapping microstructural features in pathological tissues

Wan,

Dong,

Yao

et al. 2023

Commun Eng

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In histopathology, doctors identify diseases by characterizing abnormal cells and their spatial organization within tissues. Polarization microscopy and supervised learning have been proved as an effective tool for extracting polarization parameters to highlight pathological features. Here, we present an alternative approach based on unsupervised learning to group polarization-pixels into clusters, which correspond to distinct pathological structures. For pathological samples from different patients, it is confirmed that such unsupervised learning technique can decompose the histological structures into a stable basis of characteristic microstructural clusters, some of which correspond to distinctive pathological features for clinical diagnosis. Using hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) samples, we demonstrate how the proposed framework can be utilized for segmentation of histological image, visualization of microstructure composition associated with lesion, and identification of polarization-based microstructure markers that correlates with specific pathology variation. This technique is capable of unraveling invisible microstructures in non-polarization images, and turn them into visible polarization features to pathologists and researchers.

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Section: Methodsmentioning

confidence: 99%

Unsupervised learning of pixel clustering in Mueller matrix images for mapping microstructural features in pathological tissues

Wan,

Dong,

Yao

et al. 2023

Commun Eng

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“…( 1)-( 2), where DoFP, L2, P, and L 1 represent the 3×3 MMs of the corresponding optical elements mentioned above. The optical elements were individually calibrated using a polarimeter (PAX1000, Thorlabs, United States) in a step-by-step manner before taking measurements, guaranteeing that the system errors were maintained below 1% 29,30 . To mitigate the system errors, we acquired a total of three grayscale frames per second to calculate the mean values 31 .…”

Section: Experimental Setup and Tissue Samplementioning

confidence: 99%

Analysis and correction of backscattering polarimetric aberration induced by tissue surface geometry: a pilot ex-vivo study

Jiao,

Zhang,

et al. 2024

Polarized Light and Optical Angular Momentum for Biomedical Diagnostics 2024

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Polarization imaging techniques have been extensively employed in biomedical studies and clinical applications. As a comprehensive polarization representation, the Mueller matrix (MM) can provide abundant polarization-related information of biomedical samples. For quantitative information acquisition, groups of polarization basic parameters (PBPs) have been obtained through MM analysis and demonstrated as effective structural characterization tools of tissue samples. Recently, MM polarimetric endoscopy has shown great clinical diagnostic potential. For in-vivo polarimetry such as gastrointestinal MM endoscopy of human internal organ cavities, the complicated undulating tissue surface geometry delivers an inescapable occurrence of oblique incidence, which induces a prominent aberration to backscattering tissue polarimetry. Thus, quantitatively analyzing and reducing the polarimetric aberration induced by oblique incidence are crucial for in-vivo precision MM endoscopy. In this study, we quantitatively analyze the polarimetric aberration induced by tissue surface geometry on PBPs. A correlation heatmap is obtained as applicable criteria to select appropriate incident angle for different PBPs. Based on the analyzing results, we propose two aberration correction strategies of parameter selection and azimuth rotation, which are suitable for tissue samples with randomly and well-aligned fiber textures, respectively. Both strategies are demonstrated to be effective in the ex-vivo human gastric muscularis tissue experiment. The findings presented in this study can be useful to provide accurate polarization imaging results, widely applied on in-vivo polarimetric endoscopy for tissues with complicated surface topography.

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“…These linear equation expression of the relation between the measurement signal vector D and the ellipsometric parameter (Mueller matrix elements) vector M by the OCD system matrix C, are not only applied to SIPE system but also can be generally applied to any conventional OCD systems. 27,28 Without objective lens error : 𝑫 𝒕 = 𝑪 𝒕 𝑴 (6) With objective lens error : 𝑫 𝒆 = 𝑪 𝒆 𝑴 (7) The goal of our method is to make the measured erroneous signal 𝑫 𝒆 to the errorless signal 𝑫 𝒕 by using the previously calibrated objective lens error 𝑪 𝒆 . For the objective lens polarization error, we use a linear transformation F such that satisfies the following condition:…”

Section: Ellipsometric Errors Of the Objective Lensmentioning

confidence: 99%

Improving the accuracy and precision of OCD measurement by systematic error correction in self-interference pupil ellipsometry

Lee

Park

Lee

et al. 2023

Optical Measurement Systems for Industrial Inspection XIII

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To achieve high accuracy and precision in optical metrology for advanced semiconductors, it is crucial to identify and compensate for errors from optical components and environmental perturbations. In this study, we investigated the sources of the errors in the interferometric ellipsometer developed for next-generation OCD. The objective lens and beam splitters, the critical optical components of the system, are intensively investigated. The system errors induced by temperature fluctuation, wavelength inaccuracy, and defocus were quantitatively examined. We also proposed methods for compensating individual errors and analyzed the effect of the compensation. As a result of error compensation, the accuracy and precision of the system is improved by 6.9 times and 2.3 times, respectively. Although the investigation was conducted based on our interferometric ellipsometry system, the finding is not limited to this system, as these errors are commonly found in most optical metrology systems. The proposed method for error compensation will be essential strategies for various ellipsometry systems suffering from a low level of accuracy and precision.

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Comparison of different calibration methods for Mueller matrix microscopy of cells

Cited by 15 publications

References 31 publications

Unsupervised learning of pixel clustering in Mueller matrix images for mapping microstructural features in pathological tissues

Unsupervised learning of pixel clustering in Mueller matrix images for mapping microstructural features in pathological tissues

Analysis and correction of backscattering polarimetric aberration induced by tissue surface geometry: a pilot ex-vivo study

Improving the accuracy and precision of OCD measurement by systematic error correction in self-interference pupil ellipsometry

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