Cervical collagen and elastic fibers classification with Mueller matrix polarimetry (Conference Presentation)

Abstract

The uterine cervix is composed mainly of fibrous connective tissues where collagen and glycosaminoglycans are the main components. Recent work has shown that elastic fibers also contribute to the cervix's change in mechanical function during pregnancy. While cervical collagen can be visualized with non-linear optical techniques, elastic fibers cannot be uniquely identified without an extensive staining protocol. Here we propose the development of a compound Mueller Matrix microscope to image Mice cervices at different gestation points and visualize collagen and elastic fibers using a convolutional neural network (CNN) and K-nearest neighbor (K-NN) classifiers. The study demonstrates a new methodology for classifying collagen and elastic fibers in the uterine cervix that can be applied to any Mueller Matrix polarimeter once initial calibration is conducted.