P. Anta, P. Carrin, A. Formella, E. Cernadas, R. Domnguez, and F. Saborido-Rey (Spain)
Segmentation, Image analysis, Fish oocytes, Fecundity,
The study of biology and population dynamics of ﬁsh
species requires the routine estimation of fecundity in in
dividual ﬁsh in many ﬁsheries laboratories. The traditional
procedure used by ﬁsheries research is to count the oocytes
manually on a subsample of known weight of the ovary,
and to measure few oocytes under a binocular microscope.
This process can be done on a computer using an interac
tive tool to count and measure oocytes. In both cases, the
task is very time consuming, which implies that fecundity
studies are rarely conducted routinely.
We attempt to design an algorithm being able to ex
tract the oocytes in a histological image. In a previous
work , a statistical comparison of the performance of
region and edge segmentation approaches was presented.
The results have been encouraging but the edge based ap
proach needed to mark manually the centers of the cells
of interest. This paper proposes a non–guided method to
extract the cells of interest based on edge information. In
a post–processing stage, the segmentation results of the re
gion and edge approaches are combined to improve the per
formance. The rate of oocyte detection has been increased
to 82% when the demanded overlap between machine de
tection and true oocyte area is greater than 75%.