Euroimmun Medizinische Labordiagnostika Ag

Jörn Voigt

Stefan Gerlach

Christian Marzahl

Christopher Krause

Jens Krauth

Melanie Hahn

Maick Danckwardt

Winfried Stöcker

Ulf Steller

Enno Schmidt

Jens Hocke

Katja Morgenroth

Vanessa Viertel

Christian Krause

Nina Van Beek

Christoper Krause

Winfried STÖCKER

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. What further takes place is determination, on the basis of the previously determined segmentation information, of at least one sub-area of the fluorescence image that is relevant to formation of the fluorescence pattern type, determination, on the basis of the previously determined at least one sub-area, of validity information indicating a degree of a validity of the measure of confidence, and output of the measure of confidence depending on the validity information.

Method and device for detecting a presence of a fluorescence pattern type on an organ segment via immunofluorescence microscopy

There is proposed a method for detecting a binding of autoantibodies from a patient sample to double-stranded deoxyribonucleic acid usingcells by means of fluorescence microscopy, including the steps of: provision of a substrate which has multiplecells, incubation of the substrate with the patient sample which potentially has the autoantibodies, incubation of the substrate with secondary antibodies which have each been labelled with a preferably green fluorescent dye, acquisition of a fluorescence image of the substrate, identification by means of a first pretrained convolutional neural network of respective sub-images in the one fluorescence image that each represent acell, furthermore respective processing of at least one subset of the respective sub-images by means of a second pretrained convolutional neural network for determining respective binding measures which indicate a respective extent of a binding of autoantibodies in a respective kinetoplast region of a respectivecell of a respective sub-image, and determination of an overall binding measure with regard to a binding of autoantibodies from the patient sample to double-stranded deoxyribonucleic acid on the basis of the respective binding measures.

Method for detecting a binding of antibodies from a patient sample to double-stranded DNA using Crithidia luciliae cells and fluorescence microscopy

A method is useful for automated detection of antibodies in a liquid biological sample with an antigen chip having antigen spots which are applied thereon and which have an identical, common dye. The antigen spots form respective antigen spot sets which form corresponding respective, regular antigen spot patterns. Furthermore, reference spots comprising the identical dye are applied, and form a reference spot set which forms a regular reference pattern. The reference pattern differs with respect to its regularity from the antigen spot patterns. Through a first image information item which represents a color of the reference spots and of the antigen spots due to the identical, first dye and through a second image information item which represents a potential color of the antigen spots due to a second dye after an incubation, binding of antibodies of the biological sample to respective antigen types is then determined by image processing.

Method for automated detection of antibodies in a liquid biological sample using an antigen chip, and antigen chip therefor

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Luebeck, Germany

Jörn Voigt