Abstract: Exemplary embodiments provide methods, mediums, and systems for processing multiplexed image data from a fluorescence in-situ hybridization (FISH) experiment. According to exemplary embodiments, a convolutional neural network (CNN) may be applied to the image data to localize and identify hybridization spots in images corresponding to different sets of targeting probes. The CNN is configured in such a way that it is able to discriminate hybridization spots in situations that are difficult for conventional techniques. The CNN may be trained on a relatively small amount of data by exploiting the nature of the FISH codebook.