::Home|Research Profile|Biomedical Image/Signal Processing


FISH Image Analysis

FISH Image Analysis

The HER-2/neu (c-erbB2) oncogene is a tyrosine kinase receptor that is overexpressed in approximately 20-30% of high-grade invasive breast carcinomas and has been shown to be a valuable prognostic indicator. Knowing that a cancer is HER-2/neu positive helps a medical team selects the appropriate treatment. Overexpression of the protein product of HER-2/neu gene is usually a consequence of gene amplification, in which multiple copies of the gene appear through the genome. The evaluation of fluorescent in situ hybridization (FISH) images is one of the most widely used methods to determine Her-2/neu status of breast samples.

Our Method

We have developed the FISH Image Analysis system- an integrated system for the automated classification of FISH cases from breast carcinomas samples. It is a module for the Volumetric Image Processing, Analysis and Visualization software package, Eikona3D and it is supported with a user interface making it very practical and simple to use. The system was developed using the visual C++ programming language.

The system employs a two-stage algorithm for spot detection and nuclei segmentation. Combining results from multiple images taken from a slice for overall classification, the FISH signals ratio per cell nucleus are measured and cases are classified as positive or negative.

Example of the proposed system is shown in figures below. For the input image on the left, the system gives the output image on the right. The red spots are presented with red crosses, the green spots with green crosses and the perimeters of the segmented nuclei with white colour.



Relevant Publications

F. Raimondo, M. A. Gavrielides, G. Karayannopoulou, K. Lyroudia, I. Pitas, and I. Kostopoulos, “Automated evaluation of her-2/neu status in breast tissue from fluorescent in situ hybridization images”, IEEE Transactions on Image Processing, vol. 14, no. 9, pp. 1288–1299, 2005.

Z. Theodosiou, I. Kasampalidis, G. Karayannopoulou, I. Kostopoulos, P. Aretini, F. A. Cardillo, G. Bevilacqua, A. Starita, K. Lyroudia, and I. Pitas, “Evaluation of automated FISH image analysis software on 60 breast carcinoma cases”, Meeting on BioInformatics and Medical Informatics, Athens, Greece, October 4-5, 2006.

Research Projects

BioPattern - Computational Intelligence for BioPattern Analysis to Support eHealth, IST


© 2006