Abstract: A system and method for achieving more accurate results when applying an image processing task to a series of medical images of a patient, without significantly increasing processing resource. The proposed system and method is based on receiving a plurality of image sequences of a particular anatomical region, each capturing cyclical movement of an anatomical object. Each image sequence is supplied to a classifier module which employs use of one or more machine learning algorithms to derive at least one score for each image sequence indicative of predicted success or quality of a result of the image processing task if applied to the given image series. This permits an assessment to be made in advance of which of the plurality of image series is most likely to result in the best (e.g. highest quality, or greatest amount of information) results from the image processing task.

Abstract: The present invention relates to multispectral imaging. In order to improve an identification of relevant multispectral material transitions (in particular caused by injected contrast agent), an apparatus is proposed to use the local maxima of the variances and/or covariances of the intensities of the multi-channel images to locate material transitions. In comparison to gradient vectors, the local variance is not directed and not prone to noise. An alternative apparatus is proposed to use the local covariance deficits of the intensities of the multi-channel images to locate material transitions. The proposed alternative approach is independent of spatial drifts across the image volume.

Abstract: Disclosed is an apparatus for heating plastic preforms, having a transport device which transports the plastic preforms along a predetermined transport path, the transport device having a circulating transport and a plurality of holding devices for holding the plastic preforms, having a plurality of heating devices which are arranged stationarily along the transport path, in such a way that the plastic preforms transported along the transport path are heated by these heating devices, the heating devices each having a plurality of heating lamps, and the apparatus having a detection device which is configured to detect a failure of the heating lamps, wherein the apparatus has a control device which is configured to control the apparatus in dependence on a number of heating lamps detected having failed.

Abstract: A system for establishing a contour of a structure is disclosed. An initialization subsystem (1) is used for initializing an adaptive mesh representing an approximate contour of the structure, the structure being represented at least partly by a first image, and the structure being represented at least partly by a second image. A deforming subsystem (2) is used for deforming the adaptive mesh, based on feature information of the first image and feature information of the second image. The deforming subsystem comprises a force-establishing subsystem (3) for establishing a force acting on at least part of the adaptive mesh, in dependence on the feature information of the first image and the feature information of the second image. A transform-establishing subsystem (4) is used for establishing a coordinate transform reflecting a registration mismatch between the first image, the second image, and the adaptive mesh.

Abstract: A system and computer-implemented method are provided for preprocessing medical image data for machine learning. Image data is accessed which comprises an anatomical structure. The anatomical structure in the image data is segmented to obtain a segmentation of the anatomical structure as a delineated part of the image data. A grid is assigned to the delineated part of the image data, the grid representing a partitioning of an exterior and interior of the type of anatomical structure using grid lines, wherein said assigning comprises adapting the grid to fit the segmentation of the anatomical structure in the image data. A machine learning algorithm is then provided with an addressing to the image data in the delineated part on the basis of coordinates in the assigned grid. In some embodiments, the image data of the anatomical structure may be resampled using the assigned grid.

Abstract: Systems and methods are provided for generating and using statistical data which is indicative of a difference in shape of a type of anatomical structure between images acquired by a first imaging modality and images acquired by a second imaging modality. This statistical data may then be used to modify a first segmentation of the anatomical structure which is obtained from an image acquired by the first imaging modality so as to predict the shape of the anatomical structure in the second imaging modality, or in general, to generate a second segmentation of the anatomical structure as it may appear in the second imaging modality based on the statistical data and the first segmentation.

Abstract: The invention provides a method for determining a confidence value for an image segmentation. The method includes obtaining an image, wherein the image comprises a view of an anatomical structure and a model of the anatomical structure is obtained, wherein the model comprises a plurality of nodes. The image is processed to generate a plurality of image segmentation outputs, wherein each image segmentation output comprises a set of values for the view, wherein each value of the set of values is associated with a node of the plurality of nodes of the model. For each node of the model, a confidence value is determined based on the plurality of values corresponding to the node. A confidence map of the anatomical structure is generated based on the confidence value of each node.

Abstract: A rearview assembly for a vehicle is provided that includes: a housing; a rearview element configured to display images of a scene to the rear of the vehicle, the rearview element disposed in the housing; a circuit board mounted in the housing behind the rearview element, the circuit board having a substantially planar surface and a peripheral edge; and a capacitive touch zone on a surface of the housing, the capacitive touch zone comprising a conductive component mounted to the circuit board, wherein the conductive component comprises a first portion mounted to the planar surface of the circuit board and a second portion extending beyond the peripheral edge of the circuit board at an angle to the planar surface.

Abstract: An ultrasound imaging system for acquiring ultrasound images of an anatomical feature of interest in a subject, comprising a controller operable by a user and configured to: process input ultrasound images to extract anatomical data; determine a set of constraints to be applied to the ultrasound images, the constraints being spatial, temporal and/or of image quality, derived from the extracted anatomical data and/or on user input; monitor the ultrasound images, as they are received, for determining their compliance with the determined constraints; and output an indication based on the determined compliance. The user can adapt the imaging process using the feedback of these indications, and can decide to stop the process based on satisfactory indications.

Abstract: A system (100) and computer-implemented method are provided for data collection for distributed machine learning of a machine learnable model. A privacy policy data (050) is provided defining computer-readable criteria for limiting a selection of medical image data (030) to a subset of the medical image data to obfuscate an identity of the at least one patient. The medical image data is selected based on the computer-readable criteria to obtain privacy policy-compliant training data (060) for transmission to another entity. The system and method enable medical data collection at clinical sites without requiring manual oversight, and enables such selections to be made automatically, e.g., based on a request for medical image data which may be received from outside of the clinical site.

Abstract: A mechanism for determining a score indicative of a success of a segmentation of a 3D image, i.e. a success score. The mechanism proposes to obtain one or more 2D images of different target views of a target object in the 3D image, by processing a segmentation result of the 3D image. (A view of) each 2D image is classified using an automated classifier. The classification results are used to determine a success score, which may indicate, for example, whether, or how closely, the 3D segmentation result represents a ground truth segmentation result with sufficient accuracy, e.g. for clinical decision making.

Abstract: An ultrasound imaging system comprises a display for displaying a received ultrasound image. A user interface is provided for receiving user commands for controlling the ultrasound imaging process, and it receives a user input which identifies a point or region of the displayed ultrasound image. An image depth is determined which is associated with the identified point or region and the imaging process is controlled to tailor the imaging to the identified point or region.

Abstract: Disclosed herein is a medical system (100, 300) comprising a display (112) and a user interface (114). The execution of machine executable instructions (120) causes a processor (104) to: receive (200) three-dimensional medical image data (122) of an anatomical structure (128, 322); receive (202) a three-dimensional segmentation (124) with one or more reference locations (800); display (204) at least one two-dimensional slice (126) of the three-dimensional medical image data; render (206) a cross section (134) of the three-dimensional segmentation, provide (208) a control element (130) of the user interface that is configured for receiving a one-dimensional position of the at least one reference location along a predetermined one-dimensional path (806); receive (210) the one-dimensional position (137) from the control element; adjust (212) the three-dimensional segmentation (124) using the one-dimensional position; and update (214) the rendering of the cross section of the three-dimensional segmentation.

Abstract: The invention provides a method for refining a mapped surface mesh of a cardiac chamber. The method includes obtaining a mapped surface mesh of the cardiac chamber anatomy, wherein the mapped surface mesh comprises a central region representing a cardiac chamber and an outer region representing a peripheral cardiac structure connected to the cardiac chamber, and wherein the mapped surface mesh comprises a first view of an anatomical landmark within the cardiac chamber, and obtaining image data of a cardiac chamber anatomy of a subject. The central region of the mapped surface mesh is deformed based on a first segmentation algorithm configured according to one or more predetermined shape- constraints and the outer region of the mapped surface mesh is deformed based on a second segmentation algorithm configured according to the image data, thereby generating a deformed outer region. The deformed central region and the deformed outer region are then combined, thereby generating a refined mapped surface mesh.

Abstract: The invention relates to a system and computer-implemented method for enabling correction of a segmentation of an anatomical structure in 3D image data. The segmentation may be provided by a mesh which is applied to the 3D image data to segment the anatomical structure. The correction may for example involve a user directly or indirectly selecting a mesh part, such as a mesh point, that needs to be corrected. The behaviour of the correction, e.g., in terms of direction, radius/neighbourhood or strength, may then be dependent on the mesh normal direction, and in some embodiments, on a difference between the mesh normal direction and the orientation of the viewing plane.

Abstract: A mechanism for creating/synthesizing realistic training data, for training a machine-learning model, using anatomical knowledge. An anatomical model can be obtained. Information from annotated training data entries (i.e. “ground truth” information), can be used to model the anatomical variation, from the obtained model, in the population of the training data. This anatomical model can then be modified, e.g. incorporating some random factors, in order to generate one or more augmented models of realistic anatomies. The augmented anatomy is then transferred from the model domain to the data entry domain to thereby generate a new data entry or data entries for training a machine-learning model. This latter process can be achieved in various ways, e.g. using GANs, such as CycleGANs and label images, or deformation vector fields.

Abstract: An anchor rail for fixing fasteners includes a first rail part and a second rail part which are connected to one another and on each of which anchor webs are formed, wherein a channel-shaped receptacle for a head section of a fastening means is formed between a first wall of the first rail part and a second wall of the second rail part, and an inwardly projecting web is provided on the first wall and an inwardly projecting web is provided on the second wall, and the inwardly projecting webs overlap the channel-shaped receptacle at the edge side. An outwardly projecting support web projects at least in sections on the first wall and/or the second wall opposite the inwardly projecting web. A method for producing an anchor rail which can absorb particularly high forces includes forming the inwardly and outwardly projecting webs from strip-shaped blanks welded to the first and second rail parts.

Abstract: Systems and methods are provided for generating and using statistical data which is indicative of a difference in shape of a type of anatomical structure between images acquired by a first imaging modality and images acquired by a second imaging modality. This statistical data may then be used to modify a first segmentation of the anatomical structure which is obtained from an image acquired by the first imaging modality so as to predict the shape of the anatomical structure in the second imaging modality, or in general, to generate a second segmentation of the anatomical structure as it may appear in the second imaging modality based on the statistical data and the first segmentation.

Abstract: An anchoring element for casting in concrete has an anchor rail having a plurality of anchor protrusions and a strip-shaped receptacle for mounting fastening elements. At least one retaining bracket is fixed to the anchor rail, which engages over the anchor rail perpendicularly to its longitudinal direction and by means of which the anchor rail can be fixed to a formwork component. At least one flange projecting laterally from the anchor rail is formed on the retaining bracket.

Abstract: Systems and methods are provided for generating and using statistical data which is indicative of a difference in shape of a type of anatomical structure between images acquired by a first imaging modality and images acquired by a second imaging modality. This statistical data may then be used to modify a first segmentation of the anatomical structure which is obtained from an image acquired by the first imaging modality so as to predict the shape of the anatomical structure in the second imaging modality, or in general, to generate a second segmentation of the anatomical structure as it may appear in the second imaging modality based on the statistical data and the first segmentation.