The expression of left-right asymmetry in biological tissue can be described as the chirality in cell alignment. Through development this biologically conserved property can be easily appreciated as the asymmetric positioning of organs and tissues, and asymmetric looping of tissues like the GI tract and the heart. It has been previously reported that various cell phenotypes have an intrinsic, unique, and well-conserved expression of asymmetry, and that changes in chiral expression due to genetic or environmental factors have been linked to tissue malformations and various disease states. Here, a Python-based algorithm was developed to characterize chiral alignment in epithelial cells through the utilization of immunofluorescence staining and image processing techniques. Straight-lined representations of cell edges were extracted from fluorescence images, and analyzed for morphological features as well as for the alignment and polarization of individual cells and their respective nuclei. These analyses unveiled interrelationships between morphological features and polarization parameters that are impossible to obtain with conventional intensity gradient-based analysis techniques. Utilizing this algorithm, we found that individual cells and nuclei are both chirally aligned and polarized and these alignments and polarizations are conserved, with blunt ends polarized towards the borders. Furthermore, nuclei were shown to position themselves away from micropattern borders as shown in previous literature. On these CCW rings, the cells exhibiting CCW alignment tend to be larger in size and more elongated, when compared to those exhibiting CW alignment, possibly suggesting that the increased front-rear polarization enhances the intrinsic cell chirality. Therefore, individual cell morphological analysis could be a potentially effective analytical tool to reveal the biophysical mechanisms underlying epithelial chiral morphogenesis.