Abstract: A method is proposed for detecting at least one fluorescence pattern on an immunofluorescence image of a biological cell substrate, comprising the following steps: incubating the cell substrate with a liquid patient sample, which potentially includes primary antibodies, and furthermore with secondary antibodies, which are marked using a fluorescence stain, irradiating the cell substrate using excitation radiation and capturing the immunofluorescence image, determining segmentation information comprising at least one first and one second segmentation area, wherein the segmentation areas each represent a respective cell substrate area, via segmentation of the immunofluorescence image using a first neural network, determining a boundary area, which represents a transition from the first cell substrate area towards the second cell substrate area in the fluorescence image, on the basis of the segmentation information, selecting multiple partial images from the immunofluorescence image along the boundary area, dete

Abstract: A method is proposed for detecting a presence of a fluorescence pattern on an immunofluorescence image of a biological cell substrate, comprising the following steps: incubating the cell substrate with a liquid patient sample, which potentially comprises primary antibodies, and furthermore with secondary antibodies, which are marked using a fluorescence stain, irradiating the cell substrate using excitation radiation and capturing the immunofluorescence image, determining respective items of location information, which indicate respective locations of respective relevant subsections of the cell substrate in the fluorescence image, and determining respective first partial confidence measures of respective presences of the fluorescence pattern on the respective subsections by means of a first neural network on the basis of the overall fluorescence image, extracting respective image subsections, which correspond to the respective subsections of the cell substrate, from the fluorescence image on the basis of the

Abstract: There is proposed a method for detecting a presence of a fluorescence pattern type on an organ segment via immunofluorescence microscopy and digital image processing. The steps comprise: provision of the organ segment, incubation of the organ segment with a liquid patient sample, incubation of the organ segment with secondary antibodies which have been labelled with a fluorescent dye, acquisition of a fluorescence image of the organ segment in a colour channel corresponding to the fluorescent dye, and provision of the fluorescence image to a neural network. What takes place by means of the neural network is simultaneous determination of segmentation information through segmentation of the fluorescence image and, furthermore, of a measure of confidence indicating an actual presence of the fluorescence pattern type.

Abstract: A method for detecting at least one potential presence of at least one fluorescence pattern type on an organ section by means of immunofluorescence microscopy and by means of digital image processing is disclosed. An organ section is provided on a slide and the section is incubated with a liquid patient sample which potentially includes primary antibodies and with secondary antibodies which have been labelled with a fluorescent dye. A fluorescence image of the organ section is acquired. A determination is made, by segmentation of the fluorescence image by means of a first neural network, of a sub-area of the fluorescence image that is relevant to formation of the fluorescence pattern type. A determination is made, on the basis of the fluorescence image by means of a second neural network, of the measure of confidence that indicates an actual presence of the fluorescence pattern type.

Abstract: A method for detecting at least one potential presence of at least one fluorescence pattern type on an organ section by means of immunofluorescence microscopy and by means of digital image processing is disclosed. An organ section is provided on a slide and the section is incubated with a liquid patient sample which potentially includes primary antibodies and with secondary antibodies which have been labelled with a fluorescent dye. A fluorescence image of the organ section is acquired. A determination is made, by segmentation of the fluorescence image by means of a first neural network, of a sub-area of the fluorescence image that is relevant to formation of the fluorescence pattern type. A determination is made, on the basis of the fluorescence image by means of a second neural network, of the measure of confidence that indicates an actual presence of the fluorescence pattern type.