Investigation on the potential of Mueller matrix imaging for digital staining

• Main Authors: Wang, Wenfeng, Lim, Lee Guan, Srivastava, Supriya, Bok-Yan So, Jimmy, Shabbir, Asim, Liu, Quan
• Other Authors: School of Chemical and Biomedical Engineering
• Format: Article
• Language: English
• Published: 2015
• Subjects: DRNTU::Science::Medicine::Biomedical engineering
• Online Access: https://hdl.handle.net/10356/107484; http://hdl.handle.net/10220/25621; http://dx.doi.org/10.1002/jbio.201500006
• Institution: Nanyang Technological University

The original stained image (top) and the digital staining image (bottom). Digital staining based on Mueller matrix measurements and their derivatives was investigated. Mueller matrix imaging was performed at the microscopic level on gastric tissue sections. Full Mueller matrices (4 × 4) were reconstructed using recorded images, followed by the extraction of polarization parameters. The most effective parameters and their combinations were extracted from Mueller matrix elements, principal component scores and polarization parameters respectively to classify samples into three categories – i.e. cancer, dysplasia and intestinal metaplasia/normal glands for various regions of interest sizes. It was observed that two-step classification yielded higher classification accuracy than the traditional one-step classification and that pixel classification based on Mueller matrix elements yielded higher accuracy than that based on polarization parameters and derived principal components. Moreover, Mueller matrix images with a lower spatial resolution generated higher classification accuracy but those with a higher spatial resolution revealed more morphological details.ns.