A. Chaddad et al. / J. Biomedical Science and Engineering 6 (2013) 1029-1033 1033
Thereby, shape features can be used to make the classi-
fication of cancerous cells b ased on morphological image
processing, i.e. the shape features in this paper. Never-
theless, the cancer continuum is still a complex subject in
which most laboratory research focuses on distinguishing
between the cancer stages [18]. Unfortunately, the transi-
tion from one stage to the next is still unclear.
4. CONCLUSION
This paper proposed a method of carcinoma cancer cell
detection using shape features and the nearest neighbour
classifier technique. Shape features showed promising
results for carcinoma cells detection. The three dominant
features, Area, Xor Cell-Convex and Solidity, were found
to be effective in detecting the carcinoma cells from the
other grades of cancer cells, BH and IN. Performance in-
dicators clearly describe our model as having higher ac-
curacy and thereby lower false alarm. This proposed mo-
del can be adapted to several applications in the assess-
ment of both cancer and normal cells as shape features is
one of the best methods in discriminating between cancer
and normal cells.
5. ACKNOWLEDGEMENTS
Authors would like to acknowledge the service Anapat of the CHU
hospital of the Nancy-Brabois and the Architecture of Embedded Sys-
tems and Smart Sensors (ASEC) team.
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