  We present a novel method for identification of the boundary of embryonic
cells (blastomeres) in Hoffman Modulation Contrast (HMC) microscopic images
that are taken between day one to day three. Identification of boundaries of
blastomeres is a challenging task, especially in the cases containing four or
more cells. This is because these cells are bundled up tightly inside an
embryo's membrane and any 2D image projection of such 3D embryo includes cell
overlaps, occlusions, and projection ambiguities. Moreover, human embryos
include fragmentation, which does not conform to any specific patterns or
shape. Here we developed a model-based iterative approach, in which blastomeres
are modeled as ellipses that conform to the local image features, such as edges
and normals. In an iterative process, each image feature contributes only to
one candidate and is removed upon being associated to a model candidate. We
have tested the proposed algorithm on an image dataset comprising of 468 human
embryos obtained from different sources. An overall Precision, Sensitivity and
Overall Quality (OQ) of 92%, 88% and 83% are achieved.
