Nuclei Detection in HER2-SISH Histopathology Images

Automatic quantification of cell nuclei in silver-enhanced in situ hybridization (SISH) images can be of great help to pathologists to examine HER2 status based on HER2 and CEN17 biomarkers. This paper proposed an image processing-based method for nuclei detection in HER2-SISH images. We first extracted sections of the foreground image using a combination of local thresholding, morphological filtering, and expanding regions based on intensity. Then the marker-controlled watershed is applied for separating the clustered nuclei in the foreground regions. A set of nuclei marked by our collaborating pathologists on SISH-stained breast cancer images are used to measure the effectiveness of the proposed approach. HER2-SISH histo-scoring is highly dependent on the accurately identified nuclei, hence the importance of the proposed detection method. Experimental results shows very promising detection performance, with high concordance against the pathologists’ marking.