Adaptive quadtree-based segmentation of nucleus and cytoplasm in pap-smear images: a lightweight and interpretable approach for automated cytology

BackgroundAutomated analysis of Pap-smear images plays an important role in cervical cancer screening, particularly in low-resource settings where manual cytology remains labour-intensive, subjective, and prone to inter-observer variability. On the other hand, accurate segmentation of the nucleus and cytoplasm is a fundamental step in computer-aided diagnosis systems because it enables quantitative morphometric analysis and computation of clinically important biomarkers such as the nucleus-to-cy