摘要:
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.
摘要:
A system and method are provided for volume rendering of image data of an image volume. A segmentation model is applied to the image data of the image volume, thereby delineating a sub-volume of the image volume. The image data inside the sub-volume is volume rendered. A user interface is provided which enables a user to interactively adjust the sub-volume by applying at least one of: a push action and a pull action to the sub-volume. The push action may cause part of the sub-volume to be pulled inwards, whereas the pull action may cause part of the sub-volume to be pulled outwards. The volume rendering of the sub-volume may be updated in response to a user's adjustment of the sub-volume.
摘要:
An ultrasound imaging apparatus (10) for segmenting an anatomical object in a field of view (29) of an ultrasound acquisition unit (14) is disclosed. The ultrasound imaging apparatus comprises a data interface (32) configured to receive a two-dimensional ultrasound data (30) of the object in the field of view in an image plane from the ultrasound acquisition unit and to receive a three-dimensional segmentation model (46) as a three-dimensional representation of the object from a segmentation unit (36). An image processor (34) is configured to determine a two-dimensional segmentation model (50) on the basis of the three-dimensional segmentation model and a segmentation plane (48), wherein the segmentation plane and an image plane of the two-dimensional ultrasound data correspond to each other. The image processor is configured to adapt a contour of the two-dimensional segmentation model to the two-dimensional ultrasound data on the basis of pattern detection and where the image processor is configured to provide annotated two-dimensional image data (42) on the basis of the two-dimensional ultrasound data and the adapted segmentation model aligned to the two-dimensional ultrasound data.
摘要:
The present invention relates to medical image editing. In order to facilitate the medical image editing process, a medical image editing device (50) is provided that comprises a processor unit (52), an output unit (54), and an interface unit (56). The processor unit (52) is configured to provide a 3D surface model of an anatomical structure of an object of interest. The 3D surface model comprises a plurality of surface sub-portions. The surface sub-portions each comprise a number of vertices, and each vertex is assigned by a ranking value. The processor unit (52) is further configured to identify at least one vertex of vertices adjacent to the determined point of interest as an intended vertex. The identification is based on a function of a detected proximity distance to the point of interest and the assigned ranking value. The output unit (54) is configured to provide a visual presentation of the 3D surface model. The interface unit (56) is configured to determine a point of interest in the visual presentation of the 3D surface model by interaction of a user. The interface unit 56 is further configured to modify the 3D surface model by displacing the intended vertex by manual user interaction. In an example, the output unit (54) is a display configured to display the 3D surface model directly to the user (58).
摘要:
A system and a method are provided for analyzing an image of an aortic valve structure to enable assessment of aortic valve calcifications. The system comprises an image interface for obtaining an image of an aortic valve structure, the aortic valve structure comprising aortic valve leaflets and an aortic bulbus. The system further comprises a segmentation subsystem for segmenting the aortic valve structure in the image to obtain a segmentation of the aortic valve structure. The system further comprises an identification subsystem for identifying a calcification on the aortic valve leaflets by analyzing the image of the aortic valve structure. The system further comprises an analysis subsystem configured for determining a centerline of the aortic bulbus by analyzing the segmentation of the aortic valve structure, and for projecting the calcification from the centerline of the aortic bulbus onto the aortic bulbus, thereby obtaining a projection indicating a location of the calcification as projected onto the aortic bulbus. The system further comprises an output unit for generating data representing the projection. Provided information on the accurate location of calcifications after a valve replacement may be advantageously used, for example, to effectively analyze the risk of paravalvular leakages of Transcatheter aortic valve implantation (TAVI) interventions for assessing the suitability of a patient for TAVI procedure.