TITLE:
Color Cell Image Segmentation Based on Chan-Vese Model for Vector-Valued Images
AUTHORS:
Jinping Fan, Shiguo Li, Chunxiao Zhang
KEYWORDS:
Cell Image; Color Image Segmentation; Level Set Method; Active Contour Model
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.6 No.10,
October
16,
2013
ABSTRACT: In this paper, we propose
a color cell image segmentation method based on the modified Chan-Vese model
for vectorvalued images. In this method, both the cell nuclei and cytoplasm can
be served simultaneously from the color cervical cell image. Color image could
be regarded as vector-valued images because there are three channels, red, green
and blue in color image. In the proposed color cell image segmentation method, to
segment the cell nuclei and cytoplasm precisely in color cell image, we should
use the coarse-fine segmentation which combined the auto dual-threshold method
to separate the single cell connection region from the original image, and the
modified C-V model for vectorvalued images which use two independent level set functions to separate the cell nuclei and cytoplasm
from the cell body. From the result we can see that by using the proposed
method we can get the nuclei and cytoplasm region more accurately than
traditional model.