Method for detecting a binding of autoantibodies from a patient sample to double-stranded deoxyribonucleic acid using Crithidia luciliae cells by means of fluorescence microscopy and by means of digital image processing, comprising - provision of a substrate which has multiple Crithidia luciliae cells, - incubation of the substrate with the patient sample which potentially has the autoantibodies, - incubation of the substrate with a first fluorescent dye, - incubation of the substrate with secondary antibodies which have each been labelled with a second fluorescent dye, wherein the second fluorescent dye causes a staining in those regions in which the autoantibodies from the patient sample are bound to the dsDNS in the respective kinetoplast region of the respective Crithidia luciliae, - acquisition of a first fluorescence image of the substrate in a first colour channel which corresponds to the first fluorescent dye, - acquisition of a second fluorescence image of the substrate in a second colour channel which corresponds to the second fluorescent dye, - identification of respective first sub-images in the first fluorescence image that each represent a respective Crithidia luciliae cell, - determination of respective second sub-images of the second fluorescence image that correspond to the respective first sub-images of the first fluorescence image, - respective processing of at least one subset of the respective second sub-images by means of a pretrained convolutional neural network for determining respective binding measures (IBM1, IBM2) which indicate a respective extent of a binding of autoantibodies in a respective kinetoplast region of a respective Crithidia luciliae cell of a respective second sub-image, wherein the CNN processes a respective second sub-image each separately in order to determine for a respective second sub-image a respective subordinate image representing a kinetoplast region of a respective Chritidia luciliae cell, and wherein the CNN determines the respective binding measure on the basis of the respective subordinate image, characterized in that the CNN generates, in the course of the determination of the respective individual binding measures, a respective final feature map for a respective second sub-image, that, furthermore, on the basis of the final feature map, a respective positive confidence measure with regard to a presence of the binding of autoantibodies in a respective kinetoplast region is determined for a respective second sub-image, that, furthermore, a subset of the second sub-images is selected on the basis of the respective positive confidence measures of the respective second sub-images, and that, furthermore, an overall binding measure with regard to the binding of autoantibodies from the patient sample to double-stranded deoxyribonucleic acid is determined on the basis of those binding measures which belong to the selected second sub-images of the subset. - provision of a substrate which has multiple Crithidia luciliae cells, - incubation of the substrate with the patient sample which potentially has the autoantibodies, - incubation of the substrate with a first fluorescent dye, - incubation of the substrate with secondary antibodies which have each been labelled with a second fluorescent dye, wherein the second fluorescent dye causes a staining in those regions in which the autoantibodies from the patient sample are bound to the dsDNS in the respective kinetoplast region of the respective Crithidia luciliae, - acquisition of a first fluorescence image of the substrate in a first colour channel which corresponds to the first fluorescent dye, - acquisition of a second fluorescence image of the substrate in a second colour channel which corresponds to the second fluorescent dye, - identification of respective first sub-images in the first fluorescence image that each represent a respective Crithidia luciliae cell, - determination of respective second sub-images of the second fluorescence image that correspond to the respective first sub-images of the first fluorescence image, - respective processing of at least one subset of the respective second sub-images by means of a pretrained convolutional neural network for determining respective binding measures (IBM1, IBM2) which indicate a respective extent of a binding of autoantibodies in a respective kinetoplast region of a respective Crithidia luciliae cell of a respective second sub-image, wherein the CNN processes a respective second sub-image each separately in order to determine for a respective second sub-image a respective subordinate image representing a kinetoplast region of a respective Chritidia luciliae cell, and wherein the CNN determines the respective binding measure on the basis of the respective subordinate image, characterized in that the CNN generates, in the course of the determination of the respective individual binding measures, a respective final feature map for a respective second sub-image, that, furthermore, on the basis of the final feature map, a respective positive confidence measure with regard to a presence of the binding of autoantibodies in a respective kinetoplast region is determined for a respective second sub-image, that, furthermore, a subset of the second sub-images is selected on the basis of the respective positive confidence measures of the respective second sub-images, and that, furthermore, an overall binding measure with regard to the binding of autoantibodies from the patient sample to double-stranded deoxyribonucleic acid is determined on the basis of those binding measures which belong to the selected second sub-images of the subset.