Automated fish reader using learning machines

Abstract

An automated reader for reading fluorescence in-situ hybridization signals includes one or more computer processors for receiving a digitized FISH image and executing the steps of converting colors within the image to a hue value, separately for each color extracting quantitative values to detect the presence of signals corresponding to spots and applying a plurality of algorithms to extract features from the signals to determine cell shapes and segment cells within the FISH image. After recombining the signals, the extracted features for the colors learning machines are used to classify the spots according to the color and separate merged signals of classified spots that are in close proximity to each other within the image. The classified spots are counted to determine relative frequency of colors and a report is generated providing the number of classified spots of each color.