Abstract: The invention provides a method for making anatomical measurements using a captured ultrasound image representative of the anatomical region of interest. The method comprises receiving (20) data representative of a set of points selected by a user within the image and interpreting from the points a particular anatomical measurement type which the user is intending to perform. In particular, the points are processed to identify (24) a pattern or other geometrical characteristic of the points, and the location (22) of at least one of the points within the image is also identified. These two characteristics are used to identify from the set of points which measurement the operator is performing. Once the measurement is identified, an appropriate measurement template (26) is selected and applied in order to derive (30) from the set of points an anatomical measurement.

Abstract: A method for identifying a material boundary within volumetric image data is based on use of a model boundary transition function, which models the expected progression of voxel values across the material boundary, as a function of distance. Each voxel is taken in turn, and voxel values within a subregion surrounding the voxel are fitted to the model function, and the corresponding fitting parameters are derived, in addition to a parameter relating to quality of the model fit. Based on these parameters for each voxel, for each of at least a subset of the voxels, a candidate spatial point is identified, estimated to lie on the material boundary within the 3-D image dataset. The result is a cloud of candidate spatial points which spatially correspond to the outline of the boundary wall. Based on these, a representation of the boundary wall can be generated, for example a surface mesh.

Abstract: A system for generating ultrasound data in respect of an anatomical body being scanned makes use of a predetermined scan protocol, which specifies a sequence of types of ultrasound scan of structures of interest. These types may for example be different imaging modalities (static, dynamic, 2D, 3D etc.) which are most appropriate for viewing different structures within the anatomical body. From received ultrasound images, a model is used to identify the structures of interest within the ultrasound images. The best images for creating the types of scan of the protocol are then identified and a sequence is compiled of those best images. In this way, a sequence is created which combines different types of scan, in a structured way according to a predetermined protocol. This makes the analysis of the sequence most intuitive for a user, and simplifies comparison between different sequences.

Abstract: Presented are concepts for obtaining a confidence measure for a machine learning model. One such concept process input data with the machine learning model to generate a primary result. It also generate a plurality of modified instances of the input data and processes the plurality of modified instances of the input data with the machine learning model to generate a respective plurality of secondary results. A confidence measure relating to the primary result is determined based on the secondary results.

Abstract: The present invention relates to edge restoration. In order to improve a restoration of the artificially created cleansed edges, an apparatus is proposed to automatically restore image edges after digital subtraction of digital material substitution to optimally resemble image edges in unmodified locations. The appearance of edges is machine-learned in an unsupervised non-analytical way from unmodified locations, and then, after digital suppression or digital material substitution, applied to the artificially created cleansed edges.

Abstract: The invention relates to a system for assessing a pulmonary image which allows for an improved assessment with respect to lung nodules detectability. The pulmonary image is smoothed for providing different pulmonary images (20, 21, 22) with different degrees of smoothing, wherein signal values and noise values, which are indicative of the lung vessel detectability and the noise in these images, are determined and used for determining an image quality being indicative of the usability of the pulmonary image to be assessed for detecting lung nodules. Since a pulmonary image shows lung vessels with many different vessel sizes and with many different image values, which cover the respective ranges of potential lung nodules generally very well, the image quality determination based on the different pulmonary images with different degrees of smoothing allows for a reliable assessment of the pulmonary image's usability for detecting lung nodules.

Abstract: The invention refers to an apparatus (110) for generating an augmented image comprising a) a base image providing unit (111), wherein the base image is generated based on a combination of spectral image data, b) a contrast image providing unit (112), wherein the contrast image is generated based on a different combination of the spectral image data, c) a degree of saliency determination unit (113), wherein the degree of saliency is indicative of a difference between an image value of a voxel of the contrast image and an image value of a corresponding voxel of a predetermined template image, and d) an augmented image generation unit (114) for generating an augmented base image of the object by augmenting voxels of the base image based on the degree of saliency. The invention allows to provide the augmented base image with an improved image quality and information content.

Abstract: An apparatus (10) for assessing radiologist performance includes at least one electronic processor (20) programmed to: during reading sessions in which a user is logged into a user interface (UI) (27), present (98) medical imaging examinations (31) via the UI, receive examination reports on the presented medical imaging examinations via the UI, and file the examination reports; and perform a tracking method (102, 202) including at least one of: (i) computing (204) concurrence scores (34) quantifying concurrence between clinical findings contained in the examination reports and corresponding computer-generated clinical findings for the presented medical imaging examinations which are generated by a computer aided diagnostic (CAD) process miming as a background process during the reading sessions; and/or (ii) determining (208) reading times (38) for the presented medical imaging examinations wherein the reading time for each presented medical imaging examination is the time interval between a start of the prese

Abstract: An ultrasound imaging system includes a processor circuit in communication with an ultrasound transducer configured to receive three-dimensional ultrasound data of an anatomy, and generate a target image corresponding to a target image plane of the anatomy, and a plurality of adjacent images corresponding to image planes adjacent to the target image plane along a simulated motion path. The processor circuit is further configured to display the target image, receive a user input representative of a direction of motion along the simulated motion path, and display an adjacent image of the plurality of adjacent images corresponding to the direction of motion. Accordingly, the user can observe the target image in its spatial context by scanning through the target image and one or more adjacent images on the display as if the ultrasound transducer were being scanned along the simulated motion path.

Abstract: A method and system for mapping boundary detecting features of at least one source triangulated mesh of known topology to a target triangulated mesh of arbitrary topology. A region of interest in a volumetric image associated with each triangle of the target triangulated mesh is provided to a feature mapping network. The feature mapping network assigns a feature selection vector to each triangle of the target triangulated mesh. The associated region of interest and assigned feature selection vector for each triangle of the target triangulated mesh are provided to a boundary detection network. A predicted boundary based on features of the associated region of interest selected by the assigned feature selection vector is obtained from the boundary detection network.

Abstract: Presented are concepts for initialising a model for model-based segmentation of an image which use specific landmarks (e.g. detected using other techniques) to initialize the segmentation mesh. Using such an approach, embodiments need not be limited to predefined model transformations, but can initialise a segmentation mesh with arbitrary shape. In this way, embodiments may provide for an image segmentation algorithm that not only delivers a robust surface-based segmentation result but also does so for strongly varying target structure variations (in terms of shape).

Abstract: A system for recording ultrasound images comprises a memory comprising instruction data representing a set of instructions and a processor configured to communicate with the memory and to execute the set of instructions. The set of instructions, when executed by the processor, cause the processor to receive a data stream of two dimensional images taken using an ultrasound transducer and determine from the data stream that a feature of interest is in view of the transducer. The set of instructions further cause the processor to trigger an alert to be sent to a user to indicate that the feature of interest is in view of the transducer, and send an instruction to the transducer to trigger the transducer to capture a three dimensional ultrasound image after a predetermined time interval.

Abstract: The invention provides for a medical imaging system (700) comprising: a memory (734) for storing machine executable instructions (740), a display (732) for rendering a user interface (800), and a processor (730). Execution of the machine executable instructions causes the processor to receive (1000) three dimensional medical image data (746) descriptive of a region of interest (709) of a subject (718). The region of interest comprises a spine (200). Execution of the machine executable instructions further causes the processor to receive (1002) a set of spinal coordinate systems (748) each descriptive of a location and an orientation of spinal vertebrae in the three dimensional medical image data. The set of spinal coordinate systems further comprises a set of spine centerline positions (102) each positioned on a spine centerline (108).

Abstract: The present invention provides an improved ultrasound imaging system arranged to evaluate a set of acquired 3D image data in order to provide a compounded 3D image of a fetus irrespective of its position and movement.

Abstract: Iterative material decomposition of multispectral image data includes providing a plurality of spectral images of a region of interest comprising a body part and a plurality of sets of material coefficients for a plurality of materials. Each spectral image is decomposed into a plurality of material images and an offset image. At least one of the material images for each spectral image is manipulated on the basis of at least one topological constraint relating to the body part to determine for each spectral image an updated plurality of material images and an updated offset image. A plurality of spectral images is then recomposed from the corresponding updated plurality of material images and the updated offset. Intensities at image locations are compared, and the updated plurality of material images is modified. The steps are repeated until convergence, and at least one of the recomposed spectral images at convergence is output.

Abstract: There is provided a computer implemented method (200) for medical image processing. The method comprises providing (202) a database of medical images and providing (204) an initial machine learning model which is trained for segmenting or classifying a medical feature in the medical images. The method also comprises extracting (206) a subset of medical images from the database based on a similarity score of the medical images and training (208) the machine learning model using the extracted subset of medical images in order to provide a refined machine learning model.

Abstract: An image processing system and related method. The system comprises an input interface (IN) configured for receiving an n[?2]-dimensional input image with a set of anchor points defined in same, said set of anchor points forming an input constellation. A constellation modifier (CM) is configured to modify said input constellation into a modified constellation. A constellation evaluator (CE) configured to evaluate said input constellation based on said hyper-surface to produce a score. A comparator (COMP) is configured to compare said score against a quality criterion. Through an output interface (OUT) said constellation is output if the score meets said criterion. The constellation suitable to define a segmentation for said input image.

Abstract: Presented are concepts for obtaining a confidence measure for a machine learning model. One such concept process input data with the machine learning model to generate a primary result. It also generate a plurality of modified instances of the input data and processes the plurality of modified instances of the input data with the machine learning model to generate a respective plurality of secondary results. A confidence measure relating to the primary result is determined based on the secondary results.

Abstract: A three-dimensional virtual endoscopy rendering of a lumen of a tubular structure is based on both non-spectral and spectral volumetric imaging data. The three-dimensional virtual endoscopy rendering includes a 2-D image of a lumen of the tubular structure from a viewpoint of a virtual camera of a virtual endoscope passing through the lumen. In one instance, the three-dimensional virtual endoscopy rendering is similar to the view which is provided by a physical endoscopic video camera inserted into the actual tubular structure and positioned at that location. The non-spectral volumetric image data is used to determine an opacity and shading of the three-dimensional virtual endoscopy rendering. The spectral volumetric image data is used to visually encode the three-dimensional virtual endoscopy rendering to visually distinguish an inner wall of the tubular structure and structure of interest on the wall.

Abstract: The present invention relates to an ultrasound diagnosis apparatus (10), in particular for analyzing a fetus (62). An ultrasound data interface (66) is configured to receive 3D (three dimensional) ultrasound data from an object (12). The ultrasound diagnosis apparatus further comprises a measurement unit (70) for measuring anatomical structures of the object based on the segmentation data and a calculation unit (72) configured to calculate at least one biometric parameter based on the 3D ultrasound data.