Open AccessComparison between image texture and polarization features in histopathology
Author(s) -
Yudi Liu,
Yonggui Dong,
Lu Si,
Ruoyu Meng,
Yanmin Dong,
Hui Ma
Publication year - 2021
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.416382
Subject(s) - artificial intelligence , polarization (electrochemistry) , image texture , pattern recognition (psychology) , computer science , image resolution , correlation , computer vision , image processing , optics , mathematics , physics , image (mathematics) , chemistry , geometry
Digital pathology has shown great importance for diagnostic purposes in the digital age by integrating basic image features into multi-modality information. We quantify the degree of correlation between the multiple texture features from H&E images and polarization parameter sets derived from Mueller matrix images of the same sample to provide more microstructural information for assisting diagnosis. The experimental result shows the correlations between texture feature and polarization parameter via Pearson coefficients. Polarization parameters t 1 , D L and the depolarization parameter Δ correlated with image texture features Tamura_Fcon and Tamura_Frgh , and can be used as powerful tools to quantitatively characterize cell nuclei related with tumor progression in breast pathological tissues. Polarization parameters δ and r L associated with the image texture feature Tamura_Flin have great potential for the quantitative characterization of proliferative fibers produced by inflammation. Furthermore, polarization parameters have the advantages of stable recognition in low resolution images. This work validates the associations between image texture features and polarization parameters and the merit of polarization imaging methods in low-resolution situations.