Wasswa, WilliamWare, AndrewBasaza-Ejiri, Annabella HabinkaObungoloch, Johnes2022-11-022022-11-022021William, W., Ware, A., Basaza-Ejiri, A. H., & Obungoloch, J. (2021). Automated Segmentation of Nucleus and Cytoplasm of Cervical Cells from Pap-smear Images using A Quadtree Decomposition Approach.https://doi.org/10.21203/rs.3.rs-955958/v2https://nru.uncst.go.ug/handle/123456789/5132Digital 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.enCell Segmentation, Quadtree, Pap-smear, Cervical cancer,Article