Abstract: A method for locating or identifying components or elements based on which a medical findings report can be produced for a patient to be assessed includes: providing a plurality of comparison datasets, each comparison dataset having at least one reference medical findings report; providing an analysis function, which is configured to ascertain, for a medical dataset of the patient being assessed, at least one reference dataset from the plurality of comparison datasets; ascertaining at least one reference dataset from the plurality of comparison datasets by applying the analysis function to the medical dataset and the comparison datasets; identifying at least one document model structure for the patient to be assessed based on the at least one reference medical findings report associated with the at least one reference dataset; and providing the at least one document model structure for further processing.

Abstract: Systems and computer-implemented methods are provided for identifying a template data structure for a medical report based on a medical image data set. The computer-implemented method includes: receiving a medical image data set of a patient; generating a representation of the medical image data set for display via a user interface; providing the representation for displaying to the user via the user interface; receiving, via the user interface, input directed to a medical finding visible in the representation; predicting a finding type of the medical finding based on the input; performing a lookup operation in a database to identify a template data structure for a medical report corresponding to the predicted finding type; and providing the template data structure.

Abstract: A computer-implemented method comprises: reading in sensor data relating to an image file; assigning the sensor data to a first position of a patient's anatomical structure; extracting at least one second position of the patient's anatomical structure from a medical diagnostic report; comparing the first position and the at least one second position; and outputting a warning signal if the comparison does not yield a match.

Abstract: In a computer-implemented method for providing a patient-specific medical action recommendation, a data record of the patient is received, and based on the data record, one or more observables are automatically determined. The one or more observables describe a clinical condition of the patient. The one or more observables are displayed via a user interface, and user input regarding the displayed one or more observables is received via the user interface. Based on the user input and, optionally, the data record, an action recommendation is provided to the user regarding further steps for diagnosing/treating the patient. An action recommendation device and a clinical examination and treatment system are also described.

Abstract: A system is used to control operation of a user device. An association between a medical condition and one or more decision trees is maintained. Each decision tree includes nodes organised in a tree structure originating at a root node and terminating at leaf nodes via branch nodes. The nodes are linked to each other via outputs and each output causes the system to differently control operation of the user device. Responsive to receiving medical information associated with the patient, using the association, a decision tree is identified. For the root node of the identified decision tree: a first node is selected, responsive to receiving data indicative of a first output regarding the root node; the user device is caused to retrieve medical information from one or more data sources based on the first node; and the retrieved medical information is caused to be displayed on the user device.

Abstract: A system is used to control operation of a user device. An association between a medical condition and one or more decision trees is maintained. Each decision tree includes nodes organised in a tree structure originating at a root node and terminating at leaf nodes via branch nodes. The nodes are linked to each other via outputs and each output causes the system to differently control operation of the user device. Responsive to receiving medical information associated with the patient, using the association, a decision tree is identified. For the root node of the identified decision tree: a first node is selected, responsive to receiving data indicative of a first output regarding the root node; the user device is caused to retrieve medical information from one or more data sources based on the first node; and the retrieved medical information is caused to be displayed on the user device.

Abstract: A computer-implemented method for providing information about a state of health of a patient may include: receiving a plurality of patient information of the patient by means of an interface, ascertaining health information about the patient by means of a computing unit as a function of the plurality of patient information and a first function, and checking whether a trigger condition is fulfilled based on the ascertained health information about the patient, as well as providing the ascertained health information about the patient as a function of the trigger condition.

Abstract: Methods and apparatuses are provided for identifying possible further (histo)pathological examinations from already existing histopathological examination results with a computer-implemented and automated analysis. The already existing histopathological examination results in this case are available in the form of a histopathology dataset. The histopathology dataset has one or more first histopathology slide images, which each show a first tissue slide prepared from a tissue sample of a patient and stained with a first histopathological staining. Via an analysis algorithm examination information is established based on the histopathology dataset, with the examination information having a specification for carrying out a further (histo)pathological examination of the patient, in particular by a user making an appraisal.

Abstract: A computer-implemented method and apparatus are for processing medical cases. In an embodiment, the data set that is assigned to a medical case is received. A priority for processing the medical case is then determined for the medical case by applying to the data set trained functions that have been trained using training data sets and relevant known training priorities.

Abstract: Methods as well as systems are provided for analysis of histopathology image data. In an embodiment, a method, for provision of similarity information regarding different histopathology images of a patient, includes: provisioning first histopathology image data, based on a tissue sample taken from a patient at a first point in time; provisioning second histopathology image data, based on a tissue sample taken from the patient at a second point in time, different from the first point in time; analyzing, using an image processing algorithm, the first histopathology image data and the second histopathology image data for a similarity between at least one region from the first histopathology image data indicating a pathological appraisal and at least one region from the second histopathology image data indicating a pathological appraisal; determining similarity information based on the analyzing of the image processing algorithm for the similarity; and provisioning the similarity information determined.

Abstract: A method and system are for identification of at least one medical reference image. An embodiment of the method includes providing a medical representation image based on a current examination image depicting a body part of a first patient; defining a region of interest in the medical representation image; generating a feature signature, at least for the region of interest; comparing the medical representation image with a plurality of medical images of at least one second patient stored in a medical image database, based on the feature signature generated; and identifying at least one medical image in the medical image database as the at least one medical reference image, the at least one medical reference image providing a similarity degree to the medical representation image above a threshold. In an embodiment, the generating is performed using a trained machine-learning algorithm.

Abstract: A computer-implemented method for identifying pathological changes in follow-up medical images is provided. In an embodiment, the method includes: providing reference image data showing a body part of a patient at a first time; providing follow-up image data showing a body part of a patient at a subsequent second time; generating one or more deformation fields for the reference image data and the follow-up image data describing anatomical deformations in the body part between the reference image data and the follow-up image data using at least one image registration; aligning the reference image data and the follow up image data using the one or more deformation fields to generate co-aligned image data; analyzing the co-aligned image data to identify pathological changes in the body part from the reference image data to the follow image data using a machine learned network trained to recognize pathological relevant changes in co-aligned image data.

Abstract: A system is for supporting evaluation of a medical image data set. The system includes an interface unit to provide a display of a medical image data set, visualize an evaluation tool, visualize at least one result of an evaluation function, and receive user input relating to navigating the evaluation tool in the medical image data set to a region of interest, and selecting at least one of the evaluation functions. The system further includes a computing unit to process the user input to navigate the evaluation tool, perform the at least one evaluation function, and generate a visualization of at least one result of the evaluation function. The at least one result is adapted to be visualized as an overlay to the displayed image data set and/or evaluation tool.

Abstract: In a control method for a screen display of a medical imaging system, an image data set of a patient is acquired and a comparison of the acquired image data set is made with a number of pre-stored image data sets, each of which is stored with layout parameters for the screen display associated therewith. Display of the acquired image data set take place with the layout parameters of the pre-stored image data set that has the greatest similarity with the acquired image data set.

Abstract: A system is for supporting evaluation of a medical image data set. The system includes an interface unit to provide a display of a medical image data set, visualize an evaluation tool, visualize at least one result of an evaluation function, and receive user input relating to navigating the evaluation tool in the medical image data set to a region of interest, and selecting at least one of the evaluation functions. The system further includes a computing unit to process the user input to navigate the evaluation tool, perform the at least one evaluation function, and generate a visualization of at least one result of the evaluation function. The at least one result is adapted to be visualized as an overlay to the displayed image data set and/or evaluation tool.

Abstract: A method and system are for identification of at least one medical reference image. An embodiment of the method includes providing a medical representation image based on a current examination image depicting a body part of a first patient; defining a region of interest in the medical representation image; generating a feature signature, at least for the region of interest; comparing the medical representation image with a plurality of medical images of at least one second patient stored in a medical image database, based on the feature signature generated; and identifying at least one medical image in the medical image database as the at least one medical reference image, the at least one medical reference image providing a similarity degree to the medical representation image above a threshold. In an embodiment, the generating is performed using a trained machine-learning algorithm.

Abstract: A system is used to control operation of a user device. An association between a medical condition and one or more decision trees is maintained. Each decision tree includes nodes organised in a tree structure originating at a root node and terminating at leaf nodes via branch nodes. The nodes are linked to each other via outputs and each output causes the system to differently control operation of the user device. Responsive to receiving medical information associated with the patient, using the association, a decision tree is identified. For the root node of the identified decision tree: a first node is selected, responsive to receiving data indicative of a first output regarding the root node; the user device is caused to retrieve medical information from one or more data sources based on the first node; and the retrieved medical information is caused to be displayed on the user device.

Abstract: In a control method for a screen display of a medical imaging system, an image data set of a patient is acquired and a comparison of the acquired image data set is made with a number of pre-stored image data sets, each of which is stored with layout parameters for the screen display associated therewith. Display of the acquired image data set take place with the layout parameters of the pre-stored image data set that has the greatest similarity with the acquired image data set.

Abstract: An embodiment of the invention relates to a method of visualization, wherein a 2D transformed image is generated based on 3D image data. A corresponding computation unit, a system including a computation unit and a displaying unit, a medical imaging device, and a computer program are also disclosed. The method of visualization of an embodiment includes receiving 3D image data representing at least a portion of a spine and a plurality of ribs; and generating a 2D transformed image based on the three-dimensional image data, the 2D transformed image representing the plurality of ribs and the portion of a spine in a straightened configuration, and the angle of rotation of at least one of the ribs around its long axis being selected from a plurality of angles. Selecting an angle of rotation from a plurality of angles allows selecting the perspective for viewing the ribs in the 2D transformed image.

Abstract: An embodiment of the invention relates to a method of visualization, wherein a 2D transformed image is generated based on 3D image data. A corresponding computation unit, a system including a computation unit and a displaying unit, a medical imaging device, and a computer program are also disclosed. The method of visualization of an embodiment includes receiving 3D image data representing at least a portion of a spine and a plurality of ribs; and generating a 2D transformed image based on the three-dimensional image data, the 2D transformed image representing the plurality of ribs and the portion of a spine in a straightened configuration, and the angle of rotation of at least one of the ribs around its long axis being selected from a plurality of angles. Selecting an angle of rotation from a plurality of angles allows selecting the perspective for viewing the ribs in the 2D transformed image.