Abstract: The invention relates to a method for operating a visualization system in a surgical application, wherein at least one image representation of a region to be operated on and/or operated on is captured by means of a capturing device, wherein the at least one image representation is displayed on a main display device, wherein a pose of a visualization device that can be worn on the head relative to a display surface of the main display device is captured by means of a pose sensor system, and wherein at least one three-dimensional augmentation information item corresponding to the at least one image representation displayed is generated and/or provided and is displayed on a display device of the visualization device, wherein the augmentation information item is generated and/or provided in consideration of the captured pose in such a way that the at least one image representation displayed on the main display device is extended into a three-dimensional region by the at least one three-dimensional augmentation in

Abstract: A computer-implemented method for predicting digital fluorescence images is presented. The method comprises capturing a first digital image of a tissue sample by means of a microsurgical optical system with a first digital image capturing unit with a first plurality of color channel information using white light and at least one optical filter, as well as, predicting a second digital image in the form of a digital fluorescence representation of the captured first digital image by means of a trained machine learning system comprising a trained learning model for predicting a corresponding digital fluorescence representation of an input image. Thereby, the first captured digital image is use as input image for the trained machine learning system, and parameter values of the at least one optical filter have been determined during training of the machine learning system.

Abstract: The invention relates to a method for operating a microsurgical visualization system, wherein the microsurgical visualization system comprises at least one camera for capturing a capture region and at least one illumination source for illuminating at least a part of the capture region, wherein a presence of an eye area of a patient in an image captured by means of the at least one camera is identified, wherein a region in the captured image illuminated by the at least one illumination source is identified and/or the illuminated region is determined, and wherein an irradiance is reduced, at least in the identified eye area, by controlling the at least one illumination source if an overlap between the eye area and the illuminated region is ascertained. The invention also relates to a microsurgical visualization system.

Abstract: To simplify the optical calibration of an optical observation apparatus, a stand for an optical observation unit including a calibration object arranged directly on the stand in a fixed location is specified. Moreover, an optical observation apparatus, which includes such a stand and an optical observation unit connected to the stand, a method for calibrating such an optical observation apparatus, and a computer program are specified.

Abstract: A computer-implemented method for increasing a training data volume for a machine learning system for determining an initial refractive power value for an intraocular lens to be inserted is described. The method includes measuring a group of ophthalmological biometry data of a patient and determining an initial refractive power value for the intraocular lens to be inserted by a trained machine learning system. The measured ophthalmological biometry data and a postoperative target refraction value are used as input data for the trained machine learning system. The method also includes measuring a postoperative refractive results value, assigning the postoperative refractive results value to the measured ophthalmological biometry data of the patient, and determining an importance indicator value for the new training data record.

Abstract: A computer-implemented method for determining the refractive power of an intraocular lens includes providing a physical model for determining refractive power and training a machine learning system with clinical ophthalmological training data and associated desired results to form a learning model for determining the refractive power. A loss function for training includes: a first component taking into account clinical ophthalmological training data and associated and desired results and a second component taking into account limitations of the physical model wherein a loss function component value is greater the further a predicted value of the refractive power during the training is from results of the physical model with the same clinical ophthalmological training data as input values. Moreover, the method includes providing ophthalmological data of a patient and predicting the refractive power of the intraocular lens to be used by means of the trained machine learning system.

Abstract: A head-mounted visualization unit is provided with an at least partially light-transmissive optical system. The optical system has a first optical channel assigned to a first eye of a user and a second optical channel assigned to a second eye of the user. The first optical channel is substantially transmissive to optical radiation of a first polarization and substantially opaque to optical radiation of a second polarization, with the first polarization substantially orthogonal to the second polarization. The second optical channel is substantially transmissive to optical radiation of the second polarization and substantially opaque to optical radiation of the first polarization. A polarizer and a light attenuator are arranged in the first optical channel. The light attenuator is arranged downstream of the polarizer in a direction toward the first eye of the user.

Abstract: A method for correcting a shading in a digital image of a three-dimensional observation object obtained by at least one image sensor of an optical observation device is provided. The three-dimensional observation object is illuminated by illumination light and an intensity distribution, and an inhomogeneity in an image brightness is present in the digital image of the three-dimensional observation object. The method includes ascertaining a topography of the three-dimensional observation object, correcting the inhomogeneity in the image brightness of the digital image based on the topography of the three-dimensional observation object and the intensity distribution of the illumination light. In addition, an optical observation system is provided to perform the method.

Abstract: A computer-implemented method for training a machine learning system to determine an expected offset for a physical postoperative lens position of an intraocular lens to be inserted. The method includes determining a plurality of theoretical positions in the eye of different intraocular lenses to be inserted, the determination including a respective use of a relation and a respective lens-specific constant for the plurality of the theoretical postoperative positions.

Abstract: A method for training a machine learning system with an extended set of patient data is described. This method includes measuring patient data and assigning ground truth data, determining the number of data pairs E/A, determining whether the number of data pairs lies below a previously defined training data threshold value, and if this is the case, carrying out the following steps: selecting a physical-optical model; using data pairs E/A in order to determine corresponding second output vectors A? from input vectors E by means of the relation function R, determining a respective difference vector, modifying the input vectors by an ?-vector; determining third output vectors of the relation function; determining modified output vectors; and training a machine learning system by means of the modified data and the original data.

Abstract: A method for operating a microscopy system includes irradiating a region segment of a first region by a light source with light at a first wavelength ?1 and a first luminous intensity L1, determining a substance-specific parameter within the region segment as a response to being irradiated by the light source, and repeating the steps for all region segments within the first region. In addition, the disclosure relates to a microscopy system, and a calibration method for a microscopy system.

Abstract: A method for acquiring annotated data with the aid of surgical microscopy systems comprises obtaining desired criteria which are intended to be satisfied by desired data to be annotated, and storing the set of desired criteria in a plurality of surgical microscopy systems. In each surgical microscopy system, images are then recorded and current criteria which correspond to the recorded images are determined. The current criteria are compared with the desired criteria. If the desired criteria sufficiently correspond to the current criteria, a confirmation is requested from a user as to whether said user would like to annotate data. If the user provides the confirmation, annotations for images are received from the user and stored together with the images.

Abstract: A microscopy system includes a microscope, a stand configured to mount the microscope and including a drive device configured to move the microscope, a detection device configured to detect a spatial position of a target fastened to a body part or to an instrument, wherein the position detection device includes the target with at least one marker element and an image capture device configured to optically capture the target. The microscopy system further includes at least one control device configured to operate the microscopy system according to the detected position of the target, wherein the position detection device is configured to determine the position of the target by evaluating a two-dimensional image of the image capture device. In addition, a method for operating the microscopy system is provided.

Abstract: The invention relates to a method for operating a visualization system in a surgical application, wherein a registration device of the visualization system provides a video data stream with a first image size as an output, wherein an image excerpt of the video data stream with a second image size that has been reduced in relation to the first image size is transmitted to a head-mounted visualization device via a communications link and is displayed on a display device of the visualization device, wherein a viewing direction of a user is registered by means of a sensor system, and wherein the image excerpt of the video data stream is defined on the basis of the registered viewing direction. Further, the invention relates to a visualization system.

Abstract: A method of operating a surgical microscope includes receiving an instruction to move the camera relative to the object, operating a zoom lens to zoom out and displaying images obtained by processing images recorded by the camera such that centers of the displayed images correspond to a target position within the recorded images and such that the magnification of the object displayed in the images is the initial magnification, wherein the target position is displaced within the recorded images relative to the first position, and operating actuators to move the camera.

Abstract: An apparatus for classifying a brain tissue area as functional or non-functional by a stimulation of the brain includes a receiver unit for receiving information about a performed stimulation, a recording device for recording images that represent the brain tissue area, a detection unit for detecting a change in perfusion in the brain tissue area, and a classification unit configured to determine with the information whether there is a correlation between the performed stimulation and the detected change in perfusion, and to classify the brain tissue area as functional or as non-functional. The recording device is an endomicroscope for recording endomicroscopic images of the brain tissue area with a spatial resolution better than 20 ?m and a frame rate of at least 0.4 frames per second. The detection unit is configured to detect a change in perfusion based on the positions of certain tissue structures in the recorded images.

Abstract: A method for training and using a machine learning system for a differentiation between healthy and diseased tissue during a microsurgical intervention is described. In this case, the method comprises: receiving training data and associated annotation data for training a machine learning system, training the machine learning system, which after training is configured for a prediction of a probability value and a prediction of a trustworthiness value, from which a control signal for a surgery assistance system is derivable, which is usable during a later application during a microsurgical operation, and storing parameter values of the trained machine learning model.

Abstract: A microscopy system includes a microscope, a stand configured to mount the microscope and including a drive device configured to move the microscope, a detection device configured to detect a spatial position of a target fastened to a body part or to an instrument, wherein the position detection device includes the target with at least one marker element and an image capture device configured to optically capture the target. The microscopy system further includes at least one control device configured to operate the microscopy system according to the detected position of the target, wherein the position detection device is configured to determine the position of the target by evaluating a two-dimensional image of the image capture device. In addition, a method for operating the microscopy system is provided.

Abstract: The invention relates to a method for operating a medical microscope, in particular in the field, with an interchange and/or a misalignment of at least one component of the medical microscope being followed by an identification of the interchanged and/or misaligned at least one component, with required adjustment measures and/or calibration measures being determined in automated fashion using the identified at least one interchanged and/or misaligned component as a starting point, and with the determined required adjustment measures and/or calibration measures being carried out. Furthermore, the invention relates to a medical microscope arrangement.

Abstract: Applying aerogel-containing insulation layer(s) to an article. The insulation layer comprising: aerogel particles; and at least one binder, comprising the steps of: providing the article to be coated; mixing the aerogel particles with the particles of a pulverulent binder and/or a pulverulent solid, for example expanded glass, to give a particle mixture; applying the particle mixture to the article to be coated by scattering the particle mixture onto the article to be coated; and activating the at least one binder of the at least one insulation layer, in order to provide a bond of the particle mixture to the article, wherein the aerogel particles are present in the particle mixture in a proportion of 5 to 95 percent by weight of the particle mixture.