Automatic Detection of Cells in FISH Images Using Map of Colors and Three-Track Segmentation

摘要

The article presents a complex method of recognition nuclei cells areas and of segmentation of nuclei. The evaluation process of the identification and segmentation quality of proposed methods using L2 distance function and sensitivity function is also presented. FISH test is a fluorescence technique used for staining of microscope images of breast cancer. The technique allows visualization of HER2, CEN17 genes and cells nuclei. Fast and efficient microscopy image analysis allows a proper choice of therapy. This article presents a new, complex technique based on the color analysis, morphological transformations and watershed segmentation. The technique allows rapid and efficient identification of nuclei areas, as well as precise detection of the cells nuclei outlines. This step is often overlooked in a computer image analysis, whereas it is extremely important. It allows to increase the accuracy of HER2/CEN17 gene detection, as well as it allows to exclude fake bio-markers and increase the speed of identification of algorithms for HER2 genes by limiting the searched area. Proper segmentation of nuclei also makes manual evaluation of images easier.