Computer-aided Evaluation of HER-2 Status in Fluorescent in Situ Hybridization Images

The analysis of Her-2/neu status is an
effective indicator for the diagnosis of several types of
breast carcinomas. Conventional evaluation is a difficult
task since it involves manual counting of dots in
multiple fluorescent in situ hybridization (FISH)
images. In this paper we present a multistage algorithm
for the automated evaluation of Her-2/neu status by the
analysis of FISH images from breast carcinomas. The
algorithm focuses on the detection of FISH spots and on
the cell nuclei segmentation in order to perform overall
case classification as positive or negative. Spots
detection includes mainly a top-hat filtering stage, a
binary thresholding, a 3D template matching and a grey
level contrast evaluation. Nuclei segmentation consists
of a non-linear blue channel correction step, a global
thresholding by Otsu algorithm, a grey level hole
classification by a geometric rule and of the marked
watershed transform using local h-dome maxima as
markers. By the measurement of the FISH signals ratio
per cell nucleus we perform the classification of cases.
The performances of the algorithm were evaluated with
receiver operating characteristic (ROC) analysis.