Abstract:
Candida causes fungal infections in human and animals. Since a large
number of Candida cells can be found in one sample, manual quantification
and classification has become a tedious task for technicians. Moreover, it is
used to identify fungal infections and for treatments. Therefore classification
and morphological identification of these organisms is an essential feature in
the diagnostic process. Live Candida cells appear in purple color and dead
cells appear in pink. Since Candida cells appear as overlapped cells, it is
really important to separate each touching cells and count them as
individuals. Color segmentation can be used to classify live and dead cells. It
is achieved by analyzing the red component grayscale image. The well
famous watershed method has been used for the segmentation of touching
Candida cells. The Distance Transform is used to apply watershed method
as it enables any types of intensity images. Introducing a semi-automated
system avoids the uncertainties where the user can remove the artifacts
from the final result of the system. Also seeded region growing algorithms
can be used for further segmentation if the user can select seed points
manually.
