Abstract
We carried out a systematic study on cross-polarized diffraction image (p-DI) pairs of 3098 mature red blood cells (RBCs) using optical cell models with varied morphology, refractive index (RI), and orientation. The influence of cell rotation on texture features of p-DI pairs characterized by the gray-level co-occurrence matrix (GLCM) algorithm was quantitatively analyzed. Correlations between the transverse diameters of RBCs with different RI values and scattering efficiency ratios of s- and p-polarized light were also investigated. The correlations remain strong even for RBCs with significant orientation variations. In addition, we applied a minimum redundancy maximum relevance (mRMR) algorithm to improve the performance of support vector machine (SVM) classifiers. It was demonstrated that a set of selected GLCM parameters allowed for an efficient solution of classification problems of RBCs based on morphology. For 1598 RBCs with varied shapes corresponding to normal or pathological cases, the accuracy of the SVM based classifications increased from 83.8% to 96.8% with the aid of mRMR. These results indicate the strong potential of p-DI data for rapid and accurate screening examinations of RGC shapes in routine clinical tests.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
