Automated segmentation of free-lying cell nuclei in Pap smears for malignancy-associated change analysis
Paper i proceeding, 2012

This paper presents an automated algorithm for robustly detecting and segmenting free-lying cell nuclei in bright-field microscope images of Pap smears. This is an essential initial step in the development of an automated screening system for cervical cancer based on malignancy associated change (MAC) analysis. The proposed segmentation algorithm makes use of gray-scale annular closings to identify free-lying nuclei-like objects together with marker-based watershed segmentation to accurately delineate the nuclear boundaries. The algorithm also employs artifact rejection based on size, shape, and granularity to ensure only the nuclei of intermediate squamous epithelial cells are retained. An evaluation of the performance of the algorithm relative to expert manual segmentation of 33 fields-of-view from 11 Pap smear slides is also presented. The results show that the sensitivity and specificity of nucleus detection is 94.71% and 85.30% respectively, and that the accuracy of segmentation, measured using the Dice coefficient, of the detected nuclei is 97.30±1.3%.

Cell nucleus


Cervical cancers

Watershed segmentation

Manual segmentation

Microscope images

Sensitivity and specificity

Dice coefficient

Epithelial cells

Segmentation algorithms

Automated screening

Automated algorithms

Pap smear

Gray scale

Automated segmentation

Change analysis


Ramin Moshavegh

Chalmers, Signaler och system

B. Ehteshami Bejnordi

Chalmers, Signaler och system

Andrew Mehnert

Signaler och system, Signalbehandling och medicinsk teknik, Digitala bildsystem och bildanalys

K. Sujathan

Regional Cancer Centre India

P. Malm

Uppsala Universitet

E. Bengtsson

Uppsala Universitet

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

1557170X (ISSN)

5372-5375 6347208