Automated Segmentation of Nucleus and Cytoplasm of Cervical Cells from Pap-smear Images using A Quadtree Decomposition Approach. - Wasswa, William; Ware, Andrew; Basaza-Ejiri, Annabella Habinka; Obungoloch, Johnes (Research square, 2021)
Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology especially for cervical cancer screening from pap-smears. Manual assessment of pap-smears is labour intensive and prone to interobserver variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literature. A critical prerequisite in automated analysis of pap-smears is nucleus and cytoplasm segmentation, which is the basis of cervical cancer screening. This paper articulates a potent approach to the segmentation of cervical cells into nucleus and cytoplasm using a quadtree decomposition approach with statistical measures.
Keywords: Cell Segmentation, Quadtree, Pap-smear, Cervical cancer