ArticleBiomedical optics express2020
Probing variations of fibrous structures during the development of breast ductal carcinoma tissues via Mueller matrix imaging.
Article in Biomedical optics express, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 35 citations in OpenAlex.
- Enhancing polarization contrast with depolarization mechanism using PS-OCT.Scientific reports · 2025Article
- An Overview of Invasive Ductal Carcinoma (IDC) in Women's Breast Cancer.Current molecular medicine · 2025Review
- PoLambRimetry: a multispectral polarimetric atlas of lamb brain.Journal of biomedical optics · 2024Article
- Characterization and classification of ductal carcinoma tissue using four channel based stokes-mueller polarimetry and machine learning.Lasers in medical science · 2024Article
- Machine learning based local recurrence prediction in colorectal cancer using polarized light imaging.Journal of biomedical optics · 2024Article
- Deep-learning-based cross-modality translation from Stokes image to bright-field contrast.Journal of biomedical optics · 2023Article
- Assessment of tissue pathology using optical polarimetry.Lasers in medical science · 2022Article
- Polarization enhanced laparoscope for improved visualization of tissue structural changes associated with peritoneal cancer metastasis.Biomedical optics express · 2022Article
- Probing Individual Particles in Aquatic Suspensions by Simultaneously Measuring Polarized Light Scattering and Fluorescence.Biosensors · 2021Article
- Article
- Comparative study of the influence of imaging resolution on linear retardance parameters derived from the Mueller matrix.Biomedical optics express · 2021Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recently, we developed a label-free method to probe the microstructural information and optical properties of unstained thin tissue slices based on microscopic Mueller matrix imaging technique. In this paper, we take the microscopic Mueller matrix images of human breast ductal carcinoma tissue samples at different pathological stages, and then calculate and analyze their retardance-related Mueller matrix-derived parameters. To reveal the microstructural features more quantitatively and precisely, we propose a new method based on first-order statistical properties of image to transform the 2D images of Mueller matrix parameters into several statistical feature vectors. We evaluate each statistical feature vector by corresponding classification characteristic value extracted from the statistical features of Mueller matrix parameters images of healthy breast duct tissue samples. The experimental results indicate that these statistical feature vectors of Mueller matrix derived parameters may become powerful tools to quantitatively characterize breast ductal carcinoma tissue samples at different pathological stages. It has the potential to facilitate automating the staging process of breast ductal carcinoma tissue, resulting in the improvement of diagnostic efficiency.
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Registered trials
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.