We present a region based method for segmenting and splitting
images of cells in an automatic and unsupervised manner.
The detection of cell nuclei is based on the Bradley’s method.
False positives are automatically identified and rejected based
on shape and intensity features. Additionally, the proposed
method is able to automatically detect and split touching cells.
To do so, we employ a variant of a region based multi-ellipse
fitting method (DEFA) that makes use of constraints on the
area of the split cells. The quantitative assessment of the
proposed method has been based on two challenging public
datasets. This experimental study shows that the proposed
method outperforms clearly existing methods for segmenting
fluorescence microscopy images.