About this document
Automated Cervical Cell Segmentation by Sàkâtã Ábéŕà is a document available to read on EtoBox.
This document presents a method for automatically segmenting cervical cells in Pap smear images. The method uses k-means clustering in different color spaces (RGB, HSV, L*a*b, YCbCr) to separate cells, nuclei, and cytoplasm from background. The goal is to develop an automated Pap smear analysis system to help cytotechnologists more efficiently screen for cervical cancer and pre-cancerous changes. The key steps are converting the image to different color spaces, using k-means clustering to classify pixels in
- Author
- Sàkâtã Ábéŕà
- Language
- EN