Segmentation of Overlapping Cervical Cells in Normal Pap Smear Images Using Distance-Metric and Morphological Operation
Abstract: The automatic
interpretation of Pap Smear image is one of challenging issues in some aspects.
Accurate segmentation for each cell is an important procedure that must be done
so that no information is lost during the evaluation process. However, the
presence of overlapping cells in Pap Smear image make the automated analysis of
these cytology images become more difficult. In most of the studies, cytoplasm
segmentation is the difficult stage because the boundaries between cells are
very thin. In this study, we propose an algorithm that can segment the
overlapping cytoplasm. First, the morphology operation and global thresholding
to segment cytoplasm is done. Second, the overlapping area on cytoplasm region
is separated using morphological operation and distance criteria on each pixel.
The proposed method has been evaluated against the results of manual tracing by
experts. The experiment results show that the proposed method can segment the
overlapping cytoplasm as similar as experts do, i.e., 2:897 3:632 (mean std)
using Hausdorff distance.
Author: Rahadian Kurniawan,
Izzati Muhimmah, Arrie Kurniawardhani, Indrayanti Indrayanti
Journal Code: jptinformatikagg170007
