Evidence map›Paper›PMID 39066100›Full record

ArticleSensors (Basel, Switzerland)2024

Full-Automatic High-Efficiency Mueller Matrix Microscopy Imaging for Tissue Microarray Inspection.

Hanyue Wei, Yifu Zhou, Feiya Ma, Rui Yang, Jian Liang, Liyong Ren

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Hanyue WeiSchool of Physics and Information Technology, Shaanxi Normal University, Xi'an 710119, China.
Yifu ZhouSchool of Physics and Information Technology, Shaanxi Normal University, Xi'an 710119, China.
Feiya MaSchool of Physics and Information Technology, Shaanxi Normal University, Xi'an 710119, China.
Rui YangSchool of Physics and Information Technology, Shaanxi Normal University, Xi'an 710119, China.
Jian LiangSchool of Physics and Information Technology, Shaanxi Normal University, Xi'an 710119, China.ORCID 0000-0002-0324-1497
Liyong RenSchool of Physics and Information Technology, Shaanxi Normal University, Xi'an 710119, China.ORCID 0000-0002-7547-7511

Funding

Natural Science Foundation of Shaanxi Province 2021JM-204Natural Science Foundation of Shaanxi Province 2022JQ-612Science and Technology Development Funds of Shaanxi Province 2024QCY-KXJ-179
6 · The paper itself

Abstract

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.

Indexed as

Image Processing, Computer-AssistedTissue Array AnalysisAlgorithmsFemaleHumansMicroscopyNeoplasmsReproducibility of ResultsUterine Cervical Neoplasmscancerous cervical inspectionMueller matrix microscopy imagingpolarization measurementtissue microarray

Identifiers

PMID39066100
PMCPMC11280869

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.