Abstract: A method for an optical imaging system having a scanning imaging device includes obtaining sensor data from a detector of the scanning imaging device. The sensor data include a representation of a pattern captured by the detector. The method further includes determining a characteristic geometry of the representation of the pattern, comparing the characteristic geometry with a reference geometry in order to determine a comparison result, determining at least one calibration parameter for calibrating at least one control unit for moving a beam-conducting element of the scanning imaging device based on the comparison result, and operating the at least one control unit based on the at least one calibration parameter.

Abstract: A method for determining a calibration of a microscope includes illuminating a first region of a reference object using illumination light, the reference object including multiple pattern elements arranged in a known regular pattern, the first region including a first pattern element, generating a first image of the first region, generating first image data corresponding to the first image, determining an approximate position of a second pattern element based on the first image data and the known regular pattern, determining a second region of the reference object including the a second pattern element based on the approximate position, illuminating the second region of the reference object using the illumination light, generating a second image of the second region, generating second image data corresponding to the second image, and determining parameters of the calibration for the microscope based on the first image data and the second image data.

Abstract: A computer-implemented method for training a denoising model for a microscope includes obtaining a plurality of training images with different image acquisition settings taken with the microscope, the plurality of training images including noise caused by the microscope's hardware, and training the denoising model using the plurality of training images obtained with different image acquisition settings, thereby making the denoising model specific to the microscope's hardware.

Abstract: An imaging device includes a first detector in a first path, and configured to capture a first image when no filter is inserted into the first path, a third image when a first filter is inserted into the first path, and a first actual image, a second detector in a second path, and configured to capture a second image when no filter is inserted into the second path, a fourth image when a second filter is inserted into the second path, and a second actual image, and a controller configured to determine a first misalignment between the first image and the second image, a second misalignment between the third image and the first image, and a third misalignment between the fourth image and the second image, and to align the first actual image and the second actual image based on the first misalignment, the second misalignment, and the third misalignment.

Abstract: A method for operating a light sheet microscope includes capturing an image of a volume in a camera space by exciting the volume with light sheets that are oblique relative to an optical axis of a primary lens of the light sheet microscope and are emitted at different positions in the volume and by capturing a light sheet image for each light sheet, transforming the image from the camera space to a user space by mapping information from the light sheet images to single-view focus planes, displaying the volume in the user space at a user interface, receiving a selection information in the user space about a part of the volume, retransforming the selection information from the user space to the camera space to control the light sheet microscope for capturing a selected image based on the selection information, and capturing the selected image about the part of the volume.

Abstract: A sample positioning device for a light sheet microscope includes a stage insert configured to be received by a stage of the light sheet microscope. The stage insert includes a rotatable sample holder. The rotatable sample holder includes a sample position configured to receive a sample carrier. The rotatable sample holder is configured to be rotatable around an axis of rotation that is parallel to an optical axis of the light sheet microscope, thereby enabling a rotation of a sample received by the sample carrier in a field of view of the light sheet microscope when the stage insert is received by the stage of the light sheet microscope.

Abstract: A computer-implemented image acquisition method includes receiving a user input indicating at least one quality condition. The quality condition includes a target signal-to-noise ratio associated with a plurality of regions of interest of a sample arrangement to be imaged using a fluorescence microscope. The method further includes causing the fluorescence microscope to automatically acquire, for each region of interest of the plurality of regions of interest, at least one microscopy image using illumination settings automatically determined such that the target signal-to-noise ratio is met, and generating a dataset for generating, training, validating and/or testing a machine-learning model. The dataset includes the acquired microscopy images or references thereto.

Abstract: Embodiments of the present invention relate to an optical imaging system, and to methods, systems, and computer programs for such an optical imaging system. The methods comprise obtaining first image data of an imaging device of the imaging system, the first image data comprising a representation of a pattern. The methods comprise obtaining second image data of the pattern from the imaging device after the pattern has been displaced by a stage of the optical imaging system by a distance in a dimension defined relative to the stage. The methods comprise determining an offset between the patterns of the first and second image data in two dimensions. The methods comprise calculating a conversion parameter based on the offset and the distance. A first method comprises controlling a drive unit configured to displace the stage based on the conversion parameter.

Abstract: A method of analyzing a mixed fluorescence response of a plurality of fluorophores in a microscopic sample includes reconstructing individual fluorescence responses from a mixed fluorescence response using spectral un-mixing based on reference emission spectra for fluorophores to be reconstructed, and a procedure for determining and validating reference emission spectra including providing a plurality of image acquisition settings for a sequence of images of the sample equal to, or greater than, the plurality of fluorophores and including an illumination setting for each image, acquiring the sequence of images using the plurality of image acquisition settings and storing each image together with the corresponding illumination setting, determining candidate reference emission spectra for the fluorophores to be reconstructed from the sequence of images of the sample using one or more reference emission spectra determination algorithms, and conditionally using the candidate reference emission spectra as the refe

Abstract: A multispectral microscope system includes a first detector element for capturing a first image of a sample in a first spectral channel, and at least a second detector element for capturing a second image of the sample in a second spectral channel. The first detector element includes a first detector array. The second detector element includes a second detector array different from the first detector array. The microscope system further includes a processor for determining a spatial correlation between the first and second images based on a spectral crosstalk between the first and second spectral channels and registering the first and second images based on the spatial correlation.

Abstract: Embodiments of the present invention relate to an optical imaging system, and to methods, systems, and computer programs for such an optical imaging system. The methods comprise obtaining first image data of an imaging device of the imaging system, the first image data comprising a representation of a pattern. The methods comprise obtaining second image data of the pattern from the imaging device after the pattern has been displaced by a stage of the optical imaging system by a distance in a dimension defined relative to the stage. The methods comprise determining an offset between the patterns of the first and second image data in two dimensions. The methods comprise calculating a conversion parameter based on the offset and the distance. A first method comprises controlling a drive unit configured to displace the stage based on the conversion parameter.

Abstract: A stage insert is provided. The stage insert comprises a first region for accommodating a sample holder. Further, the stage insert comprises a second region comprising a first calibration target for calibrating a first parameter of the microscope system. The stage insert also comprises a third region comprising a second calibration target for calibrating a second parameter of the microscope system.

Abstract: A method of analyzing a mixed fluorescence response of a plurality of fluorophores in a microscopic sample includes reconstructing individual fluorescence responses from a mixed fluorescence response using spectral un-mixing based on reference emission spectra for fluorophores to be reconstructed, and a procedure for determining and validating reference emission spectra including providing a plurality of image acquisition settings for a sequence of images of the sample equal to, or greater than, the plurality of fluorophores and including an illumination setting for each image, acquiring the sequence of images using the plurality of image acquisition settings and storing each image together with the corresponding illumination setting, determining candidate reference emission spectra for the fluorophores to be reconstructed from the sequence of images of the sample using one or more reference emission spectra determination algorithms, and conditionally using the candidate reference emission spectra as the refe

Abstract: A computer-implemented method for training a denoising model for a microscope includes obtaining a plurality of training images with different image acquisition settings taken with the microscope, the plurality of training images including noise caused by the microscope's hardware, and training the denoising model using the plurality of training images obtained with different image acquisition settings, thereby making the denoising model specific to the microscope's hardware.

Abstract: A multispectral microscope system includes: a first detector element for capturing a first image of a sample in a first spectral channel; at least a second detector element for capturing a second image of the sample in a second spectral channel; and a processor for determining a spatial correlation between the first and second images based on a spectral crosstalk between the first and second spectral channels and registering the first and second images based on the spatial correlation.