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Microarray Inspection  \nHanyue Wei 1,2, Yifu Zhou 1,2, Feiya Ma 1,2, Rui Yang 1,2, Jian Liang 1,2 and Liyong Ren 1,2,3, *  \nCitation: Wei, H.; Zhou, Y.; Ma, F.; Yang, R.; Liang, J.; Ren, L. FullAutomatic High-Efficiency Mueller Matrix Microscopy Imaging for Tissue Microarray Inspection. Sensors 2024, 24, 4703. [https://doi.org/10.3390/](https://doi.org/10.3390/)  \ns24144703  \nAcademic Editors: Xin Zhu and Zhenhe Ma  \nReceived: 27 June 2024  \nRevised: 17 July 2024  \nAccepted: 18 July 2024  \nPublished: 20 July 2024  \nCopyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \n1 School of Physics and Information Technology, Shaanxi Normal University, Xi’an 710119, China; [whyy24@snnu.edu.cn](whyy24@snnu.edu.cn) (H.W.); [zhouyf@snnu.edu.cn](zhouyf@snnu.edu.cn) (Y.Z.); [feiyam@snnu.edu.cn](feiyam@snnu.edu.cn) (F.M.); [yangyr@snnu.edu.cn](yangyr@snnu.edu.cn) (R.Y.); [jianliang@snnu.edu.cn](jianliang@snnu.edu.cn) (J.L.)  \n2 Xi’an Key Laboratory of Optical Information Manipulation and Augmentation (OMA), Xi’an 710119, China  \n3 Robust (Xixian New Area) Opto-Electro Technologies Co., Ltd., Xi’an 712000, China  \n* Correspondence: [renliy@snnu.edu.cn](renliy@snnu.edu.cn); Tel.: +86-(29)-8153-0793  \nAbstract: This paper proposes a full-automatic high-efficiency Mueller matrix microscopic imaging (MMMI) system based on the tissue microarray (TMA) for cancer inspection for the first time. By performing a polar decomposition on the sample’s Mueller matrix (MM) obtained by a transmissive MMMI system we established, the linear phase retardance equivalent waveplate fast-axis azimuth and the linear phase retardance are obtained for distinguishing the cancerous tissues from the normal ones based on the differences in their polarization characteristics, where three analyses methods including statistical analysis, the gray-level co-occurrence matrix analysis (GLCM) and the Tamura image processing method (TIPM) are used. Previous MMMI medical diagnostics typically utilized discrete slices for inspection under a high-magnification objective (20×–50×) with a small field of view, while we use the TMA under a low-magnification objective (5×) with a large field of view. Experimental results indicate that MMMI based on TMA can effectively analyze the pathological variations in biological tissues, inspect cancerous cervical tissues, and thus contribute to the diagnosis of postoperative cancer biopsies. Such an inspection method, using a large number of samples within a TMA, is beneficial for obtaining consistent findings and good reproducibility.  \nKeywords: Mueller matrix microscopy imaging; cancerous cervical inspection; tissue microarray; polarization measurement  \n1. Introduction  \nCervical cancer is the most common gynecological malignancy [1,2] . Conventional methods for cervical cancer detection include colposcopy [3], cervical cytology (pap smear) [4], human papilloma virus (HPV) testing [5], and biopsy [6] . However, the colposcopy, the cervical cytology, and the HPV testing methods can only assist in determining cervical abnormalities and cannot provide definitive diagnostic results. The “gold standard” for diagnosing cancerous cervical tissues remains the combination of biopsy and pathological examination. Biopsy can be performed preoperatively [7], intraoperatively [8], or postoperatively [9] . The histopathological diagnosis in the postoperative biopsy process involves three steps: firstly, multiple samples are taken from the entire lesion and its surrounding affected tissues and organs, as well as relevant lymph nodes; secondly, the collected samples ar","cbCaiv4IkJHbHHeN","https://ap.wps.com/l/cbCaiv4IkJHbHHeN","pdf",5359833,17,"English","# Introduction\n## Background on cervical cancer detection and biopsy workflow\n## Tissue microarray (TMA) as a high-throughput histology platform\n## Limitations of existing TMA detection methods","[{\"question\":\"What is the main contribution of the proposed system?\",\"answer\":\"It introduces a full-automatic high-efficiency Mueller matrix microscopic imaging (MMMI) approach that integrates with tissue microarray (TMA) for cancer inspection.\"},{\"question\":\"How does the method distinguish cancerous tissue from normal tissue?\",\"answer\":\"It performs polar decomposition on the measured Mueller matrix to extract polarization-related parameters, then applies statistical analysis, GLCM, and TIPM to separate cancerous from normal patterns.\"},{\"question\":\"Why is using TMA with low magnification important?\",\"answer\":\"The approach uses TMA to process many samples consistently and employs a low-magnification (5×) large field of view, which improves efficiency and reproducibility compared with slice-based high-magnification (20×–50×) inspection.\"}]","Full-Automatic High-Efficiency Mueller Matrix Microscopy Imaging for Tissue Microarray Inspection | PDF",1789979744,43]