Texture analysis of the endometrium during hysteroscopy: Preliminary results

Abstract

The objective of this study is to investigate the usefulness of texture analysis in the endometrium during hysteroscopy in endoscopic imaging of the uterine cavity. Endoscopy images from the endometrium from three subjects, at optimum illumination and focus, were frozen and digitized at 720×576 pixels using 24bits color. Regions of Interest (ROI) of normal (N=61) and abnormal (N=69) regions were manually selected by the physician. ROI images were converted into gray scale and Statistical Features (SF) and Spatial Gray Level Dependence Matrix features (SGLDM) were computed. The non-parametric Wilcoxon rank sum test at a = 0.05 was carried out for comparing the differences between normal and abnormal tissue. There was significant difference between normal and abnormal endometrium for the SF features variance, energy and entropy and for the SGLDM feature of angular second moment. There was no significant difference for the SF features mean, median, and SGLDM features of contrast, correlation and homogeneity.