An image processing method for detecting first and second dots representing in-situ hybridization signals of different color, the method being implemented in an image analysis system, the first and second dots being contained in a digital image of a tissue sample, the pixel intensity values of the first dots indicating in situ hybridization signals generated by a first stain having a first color, the pixel intensity values of the second dots indicating in situ hybridization signals generated by a second stain having a second color, the detection of the first and second dots in the digital image comprising: - generating a first color channel image and a second color channel image via color deconvolution of the digital image, the first color channel image corresponding to the color spectrum contribution of the first stain and the second color channel image corresponding to the color spectrum contribution of the second stain; - computing at least one DoG image from the digital image by applying a pair of Gaussian filters whose Kernels have a different standard deviation to the digital image and by subtracting the two filtered images output by the Gaussian filters from each other, the DoG image being a difference-of-Gaussian image; - computing an absorbance image from the image of the tissue sample; - detecting sets of adjacent pixels in the digital image whose absorbance values in the absorbance image exceed an absorbance threshold and whose DoG values in the DoG image exceeds an DoG threshold and using the detected sets of adjacent pixels as prospective dots; - identifying the ones of the prospective dots whose intensity values in the first color channel image exceeds a first-color-intensity threshold and outputting said identified prospective dots as the detected first dots; and - identifying the ones of the prospective dots whose intensity values in the second color channel image exceeds a second-color-intensity threshold and outputting said identified prospective dots as the detected second dots. - generating a first color channel image and a second color channel image via color deconvolution of the digital image, the first color channel image corresponding to the color spectrum contribution of the first stain and the second color channel image corresponding to the color spectrum contribution of the second stain; - computing at least one DoG image from the digital image by applying a pair of Gaussian filters whose Kernels have a different standard deviation to the digital image and by subtracting the two filtered images output by the Gaussian filters from each other, the DoG image being a difference-of-Gaussian image; - computing an absorbance image from the image of the tissue sample; - detecting sets of adjacent pixels in the digital image whose absorbance values in the absorbance image exceed an absorbance threshold and whose DoG values in the DoG image exceeds an DoG threshold and using the detected sets of adjacent pixels as prospective dots; - identifying the ones of the prospective dots whose intensity values in the first color channel image exceeds a first-color-intensity threshold and outputting said identified prospective dots as the detected first dots; and - identifying the ones of the prospective dots whose intensity values in the second color channel image exceeds a second-color-intensity threshold and outputting said identified prospective dots as the detected second dots.