Abstract: A mechanism for generating an artefact estimation image that represents the effect of cone-beam artefacts in a computed tomography (CT) image. This is achieved by identifying the position of gradients (being sudden changes of intensity) in an axis of the CT image parallel to a rotation axis of the CT system that generated the CT image, where each gradient represents a source of a cone-beam artefact. A look-up table is used to individually identify the effect of a cone-beam artefact on areas surrounding each identified position of the gradient, to generate an artefact estimation image.

Abstract: A medical image processing device includes a display device; and an electronic processor programmed to perform a medical image processing method including receiving a three dimensional (3D) medical image; computing least one 3D derivative image of the 3D medical image; identifying a set of fibers in the 3D medical image by tracing fibrous image features in the at least one 3D derivative image starting from respective seed locations in the least one 3D derivative image; and controlling the display device to display an anatomical representation comprising or derived from the set of fibers.

Abstract: A respiratory monitoring device includes an electronic controller configured to: analyze an audio signal triggered during inspiratory and expiratory phases of a patient receiving mechanical ventilation therapy from a mechanical ventilator, the audio signal being acoustically coupled into the airway of the patient, to determine resonant frequencies of the airway; determine a shift in the resonant frequencies between the inspiratory and expiratory phases to determine a presence of pendelluft inside of a lung of the patient; and output an indication of the presence of pendelluft.

Abstract: A mechanical ventilation assessment assistance device includes at least one electronic processor; and a non-transitory storage medium storing instructions readable and executable by the at least one electronic processor to perform a mechanical ventilation assessment assistance method including obtaining an image of a patient (P) receiving mechanical ventilation; generating or updating a patient-specific lung model of at least one lung of the patient based on the obtained image; simulating a response of the patient to a mechanical ventilation therapy using the generated or updated patient-specific lung model; comparing the simulated response with an actual response of the patient to the mechanical ventilation therapy; based on the comparison, determining an imaging recommendation for acquiring an image of at least one lung of the patient; and outputting the determined imaging recommendation.

Abstract: Images are processed while remaining agnostic as to an image source. An input image to be processed is retrieved. A first value or set of values for an image metric associated with the input image is determined, and a first filter is generated based on a relationship between the first value or set of values and a target value or set of values. The first filter is then applied to the input image to generate a working image having a second value or set of values for the image metric substantially similar to the target value or set of values for the image metric. The working image is processed using a standardized image processing methodology. An output is generated, which may be an image, based on the processed working image and outputs the output.

Abstract: A mechanical ventilation assistance device includes at least one electronic controller configured to receive positional data of a patient; determine a position of an imaging device configured to obtain imaging data of the patient based on the received positional data; and display, on a display device, a representation of the determined position of the imaging device.

Abstract: A mechanical ventilation device comprising at least one electronic controller configured to receive imaging data and transpulmonary pressure data associated with a lung of a patient; perform deformable image registration of the inhalation image and the exhalation image to produce a relative compliance or elasticity map of the lungs; convert the relative compliance or elasticity map of the lungs to a quantitative compliance or elasticity map of the lungs based on the inhale transpulmonary pressure and the exhale transpulmonary pressure; and display the information relating to or derived from the quantitative compliance or elasticity map on a display device.

Abstract: Systems and methods for training a machine-learning model for artifact reduction are provided. Such methods include retrieving a three-dimensional digital phantom reconstructed from CT imaging data. The method then selects a first Z position along the central axis and simulates a first set of forward projections from the digital phantom taken along an axial trajectory at the first Z position along the central axis. The first set of forward projections has a first simulated collimation in the axial direction. The method then reconstructs a first simulated image from the first set of forward projections and identifies a plurality of secondary Z positions along the central axis other than the first Z position. For each of the secondary Z positions and the first Z position itself, the method then simulates a set of secondary forward projections from the digital phantom taken along corresponding axial trajectories at the corresponding secondary Z position.

Abstract: A medical imaging device includes a display device; and at least one electronic processor programmed to perform an imaging method including controlling an associated medical imaging device to acquire a dynamic lung image including a time sequence of lung images depicting at least one lung of the patient; separating the dynamic lung image into a dynamic respiration image depicting density changes due to respiration and a dynamic perfusion image depicting density changes due to lung perfusion; at least one of: (i) generating a respiration delay image based on the dynamic respiration image; and (ii) generating a perfusion delay image based on the dynamic lung perfusion image; and displaying the respiration delay image and/or lung perfusion delay image on the display device.

Abstract: A method for use in a material decomposition procedure applied to dual-energy CT projection data. Material decomposition is often done using pre-computed lookup tables (LUTs) for mapping input projection data, acquired with particular X-ray source parameters, to material data values. However, the X-ray source parameters can vary over the course of a scan, making the results inaccurate. Embodiments are based on determining in advance a plurality of sets of basis LUTs for each of a plurality of different possible ranges of values over which the X-ray source parameter may vary during a scan. The basis LUTs in each set are devised as being LUTs which represent the majority contribution to the overall material decomposition function for the time-varying energy spectrum.

Abstract: The present invention relates to a device (10) and related method and computer-program product for planning an acquisition by a CT scanner (20). The device receives a pre-scan image of the object from the scanner via an input (12). A processor (16), in use of the device, obtains a parameter selection based on the pre-scan image, in which this parameter selection comprises at least axial upper and lower scan range limits of a region of the object to be scanned. The processor determines a value indicative of an image gradient or gradient component in the pre-scan image at the upper and/or lower scan range limit or in a predetermined neighborhood thereof. If this value exceeds a threshold, a user is informed via an output (18) that the selected scan range does not satisfy a quality criterium for reconstruction and/or a new parameter selection is determined by repositioning, resizing and/or changing an orientation of the selected region to be scanned.

Abstract: A computed tomography imaging system (102) includes an X-ray radiation source (110) configured to emit X-ray radiation that traverses an examination region (108) and an X-ray radiation sensitive detector array (112) configured to detect X-ray radiation traversing the examination region and generate a view of line integrals. The imaging system further includes a subject support table top (118) configured to translate in the examination region for a scan based on at least one scan parameter. The imaging system further includes an operator console (122), which includes a processor (128) and computer readable storage medium (130) with a scan parameter adapter module (132). The processor is configured to execute instructions of the scan parameter adapter module, which causes the processor to determine a contrast agent concentration from the view of line integrals and adjust the at least one scan parameter based on the determined concentration.

Abstract: An intubation assistance device includes an electronic controller configured to: identify, from one or more images of a patient, information about the patient including at least a diameter of a trachea and a length of an intubation pathway; determine a recommended ETT size including an ETT diameter and an ETT depth of insertion from the determined diameter of the trachea and the determined length of the intubation pathway; and display the recommended ETT size on a display device.

Abstract: An apparatus (1) for use in conjunction with a medical imaging device (2) having an imaging device controller (4) that displays a graphical user interface (GUI) (8) including a preview image viewport (9). The apparatus includes at least one electronic processor (20) programmed to: receive a video feed (17) of the GUI displayed on the imaging device controller; extract a preview image (12) displayed in the preview image viewport from the live video feed of the GUI; perform an image analysis (38) on the extracted preview image to detect one or more image features (42) indicative of one or more potential problems associated with a medical imaging examination performed with the medical imaging device; and output an alert (30) when one or more potential problems associated with the medical imaging examination is detected from the one or more image features.

Abstract: Concepts for multi-energy dark-field (DAX) and phase-contrast (PC) X-ray imaging are proposed. One such concept comprise acquiring a set of low energy images with phase stepping and a set of high energy images (with or without phase stepping). Transmission, DAX, and PC images are obtained from the phase-stepped low energy images using phase retrieval. Also, a high energy transmission image is obtained from the high energy image(s). Based on the transmission image from the low energy images and the transmission image from the high energy image(s), a modified transmission image is generated.

Abstract: A non-transitory computer readable medium stores instructions executable by at least one electronic processor to perform an ultrasound monitoring method. The ultrasound monitoring method includes receiving at least one ultrasound image of a target tissue of a patient (P) acquired using an ultrasound imaging probe positioned at a target position on the patient; determining at least one data acquisition and/or data processing parameter based on the at least one ultrasound image of the target tissue acquired using the ultrasound imaging probe; and monitoring the target tissue of the patient including acquiring tissue data of the patient using an ultrasound patch comprising at least one ultrasound transducer placed at the target position on the patient and using the at least one data acquisition and/or data processing parameter.

Abstract: The invention provides a method for data reduction in the context of spectral CT imaging. The method comprises reducing the number of spectral channels of the acquired CT data by a reduced set of synthetic energy channels, each from a weighted combination of the original measured energy channel. The weights are selected in an optimization process in which an error metric associated with an output of a material decomposition procedure to be applied to the CT data is estimated, and the weights adjusted to minimize a value of the error metric. The error might for example be a noise estimate, and/or a bias estimate.

Abstract: This invention relates to an image processing device (1) comprising an input (2) for receiving image data representative of a region of interest in the body of a patient from a medical X-ray imaging apparatus (100). The image data comprises a first dark-field image obtained for a first X-ray spectrum and a second dark-field image obtained for a second, different. X-ray spectrum. A combination unit (3) provides a combination image that is representative of a medical condition map. e.g. a lung condition map, by combining the first dark-field image and the second dark-field image.

Abstract: A diaphragm measurement device includes at least one electronic processor programmed to perform a diaphragm measurement method including receiving ultrasound imaging data of a dimension of a diaphragm of a patient during inspiration and expiration while the patient undergoes mechanical ventilation therapy with a mechanical ventilator; receiving respiratory data of the patient during inspiration and expiration while the patient undergoes the mechanical ventilation therapy; calculating a diaphragm thickness metric based on the received ultrasound imaging data of the diaphragm of the patient and the received respiratory data; and displaying, on a display device, a representation of the calculated diaphragm thickness metric.

Abstract: A non-transitory storage medium stores instructions readable and executable by at least one electronic processor to receive clinical data for a current patient (P); search a database of CT scans and/or patient-specific mechanical ventilation models for other patients using the clinical data for the current patient as a search criterion to identify a similar patient in the database and similar patient data (S) comprising a CT scan and/or a patient-specific mechanical ventilation model for the similar patient; determine a patient-specific mechanical ventilation model for the current patient based on the CT scan and/or patient-specific mechanical ventilation model for the similar patient; generate ventilator configuration data for mechanically ventilating the current patient based on the determined patient-specific mechanical ventilation model for the current patient.