Euroimmun Medizinische Labordiagnostika Ag

Melanie Hahn

Stefan Gerlach

Christian Marzahl

Christopher Krause

Jens Krauth

Joern Voigt

Maick Danckwardt

Jörn Voigt

Jens Hocke

Enno Schmidt

Nina Van Beek

Christoper Krause

Christian Krause

A method for detecting a potential presence of a fluorescence pattern type on an organ section via immunofluorescence microscopy and digital image processing, the method comprising: providing an organ section on a slide, incubating the section with a liquid patient sample potentially including primary antibodies and secondary antibodies labelled with a fluorescent dye, acquiring a fluorescence image of the organ section, determining, by segmentation of the fluorescence image via a first neural network, a sub-area of the fluorescence image relevant to formation of the fluorescence pattern type, determining, via a second neural network, the measure of confidence indicating an actual presence of the fluorescence pattern type, determining, validity information indicating a degree of a validity of the measure of confidence, and outputting the measure of confidence of the actual presence of the fluorescence pattern type and of the validity information.

Method and apparatus for detecting a presence of a fluorescence pattern type on an organ section by means of immunofluorescence microscopy

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 and apparatus are provided for detecting respective potential presences of respective different cellular fluorescence pattern types on a biological cellular substrate including human epithelioma cells (HEp cells), wherein the fluorescence pattern types include different antinuclear antibody fluorescence pattern types. A method is also provided for detecting potential presences of different cellular fluorescence pattern types on a biological cellular substrate including human epithelioma cells by means of digital image processing, as well as a computing unit, a data network device, a computer program product and a data carrier signal therefor.

Method of detecting presences of different antinuclear antibody fluorescence pattern types without counterstaining and apparatus therefor

A method is for detecting respective potential presence of respective different antinuclear antibody fluorescence pattern types on a biological cell substrate including human epithelioma cells, including: acquiring a first image which represents staining of the cell substrate by a first fluorescent dye, and acquiring a second image which represents staining of the cell substrate by a second fluorescent dye, detecting, on the basis of the first image, respective image segments which in each case represent at least one mitotic cell, selecting, on the basis of the detected image segments, subimages of the first image and subimages corresponding thereto of the second image and detecting, on the basis of the selected subimages of the first image and of the selected subimages of the second image, respective actual presence of respective cellular fluorescence pattern types by means of a convolutional neural network.

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Stockelsdorf, Germany

Melanie Hahn