Abstract: The present invention relates to a system and a method for detecting pain experienced by a patient in relation to a pose of the patient. The system comprises a pose estimation unit configured to estimate the pose of the patient and a pain detection unit configured to detect pain experienced by the patient. The system further comprises a processing unit configured to determine a correlation between the detected pain experienced by the patient and the estimated pose of the patient. The determined correlation can be displayed on a display unit to a physician.

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), includes at least one electronic processor (20) programmed to: perform an image analysis (38) on a preview image displayed in the preview image viewport to generate preview-derived image label information; extract GUI-derived image label information from the GUI excluding the preview image displayed in the preview image viewport; and output an alert (30) when the preview-derived image label information and the GUI-derived image label information are not consistent.

Abstract: Technology provides baseline images for diagnostic applications, including receiving a diagnostic image relating to a condition of a patient, the diagnostic image reflecting one of a normal state or an abnormal state of the condition, and generating a baseline image via a neural network using the diagnostic image, where the neural network is trained to generate a prediction of the diagnostic image reflecting a normal state of the condition. The neural network can include a generative adversarial network (GAN) trained only on image data with a normal state of the condition, where generating the baseline image includes an optimization process to maximize a similarity between the diagnostic image and a response of the GAN. Generating the baseline image can include selecting a portion of the diagnostic image, and adjusting a relevance weighting to be applied to the selected portion of the diagnostic image in the optimization process.

Abstract: The present invention relates to patient positioning. In order to facilitate patient positioning, an apparatus is provided that comprises an input unit, a processing unit, and an output unit. The input unit is configured to receive an X-ray image of an anatomy of interest of a patient obtained from a first image acquisition and a target set of pose parameters describing a target position of the anatomy of interest for image acquisition. The processing unit is configured to detect the anatomy of interest in the X-ray image, to determine a set of pose parameters describing a current position of the detected anatomy of interest in the first image acquisition, to determine a difference between the determined set of pose parameters and the target set of pose parameters, and to construct a trajectory that defines a sequence of sets of pose parameters for bringing the anatomy of interest from the current position to the target position, if the difference is equal to or greater than a pre-defined threshold.

Abstract: The present invention relates to medical imaging. In order to reduce repeat images, it is proposed to enable automated prediction of quality metrics prior to image formation by exploiting data from sensors. This may greatly improve the quality of medical image data acquired in the actual imaging examination, thereby leading to fewer retakes, less delayed treatment to patients, shortened workflow, and higher patient rate. In X-ray and CT exams, fewer retakes may also reduce radiation doses for patients.

Abstract: A method is provided for analyzing survey imaging data. The method comprises acquiring first image data with a first imaging protocol covering a first FOV, processing the data with an anatomical analysis program or routine to detect at least a portion of a target anatomy, and performing a coverage check adapted to determine whether the target anatomy is fully covered within the first FOV. Second image data is subsequently acquired in accordance with a second imaging protocol defining a second FOV. The second imaging protocol may be: the same as the first, but wherein the results of the coverage check are stored and linked with the second image data for later use; different to the first and wherein the results of the coverage check are output to a user interface and a user input responsive thereto is used to determine the second scan protocol; or different to the first, but wherein an adjusted second scan protocol is automatically determined.

Abstract: An X-ray imaging system (100) includes an X-ray source (110) and an X-ray detector (120) that are separated by an examination region (150) for performing an X-ray imaging operation on an object (160). A processor (140) is configured to identify (S120) one or more internal structures (180) within the object (160), based on a comparison of depth sensor data representing a three-dimensional surface (170) of the object (160), with an anatomical model comprising the one or more internal structures (180). The processor (140) is also configured to compute (S130), using the depth sensor data and the identified one or more internal structures (180), a surface projection (190) of the one or more internal structures, on the surface (170) of the object (160), from a perspective of the X-ray source (110); and to output (S140) an image representation of the surface projection (190) for displaying as an overlay on the surface (170) of the object (160).

Abstract: When performing an imaging scan on a patient, x-ray tube currents are modulated as the scan is performed. The x-ray tube current values and modulations may be recorded and accessed. The accessed values may be processed to generate overlays and displays for identifying patient and diagnostic device issues.

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: A mechanism for identifying a position of one or more anatomical landmarks in a medical image. The medical image is processed with a machine-learning algorithm to generate, for each pixel/voxel of the medical image, an indicator that indicates whether or not the pixel represents part of an anatomical landmark. The indicators are then processed in turn to predict a presence and/or position of the one or more anatomical landmarks.

Abstract: A non-transitory computer readable medium (26) stores instructions readable and executable by at least one electronic processor (20) to perform a radiology report analysis method (100). The method includes: identifying occurrences of radiology findings (36) and associated uncertainty indicators (38) in a plurality of radiology reports (32); assigning uncertainty scores (40) on a numerical scale to the identified occurrences of radiology findings based on the associated uncertainty indicators; and providing a user interface (UI) (28) on a display device (24) operatively connected with the at least one electronic processor that displays a representation (44) of the uncertainty scores assigned to the occurrences of radiology findings.

Abstract: The present invention relates to a polyamide moulding compound consisting of A 33-79.4 wt% of a polymer mixture consisting of A1 55 to 85 wt% of at least one semi-crystalline, aliphatic polyamide selected from the group PA 6, PA 46, PA 56, PA 66, PA 66/6, PA 610, PA 612, PA 6/12, PA 1010, PA 11, PA 12, PA 1012, PA 1212 and mixtures thereof; A2 15 to 45 wt% of at least one semi-aromatic polyamide selected from the group PA 6l, PA 5l/5T, PA 6l/6T, PA 10l/10T, PA 10T/6T, PA 6T/BACT/66/BAC6, PA MXD6, PA MXD6/MXDl and mixtures thereof; wherein the sum of A1 and A2 is 100 wt% of A; B 20 to 60 wt% of a reinforcing fibre; C 0.6 to 2.0 wt% metal borate, wherein the molar ratio of metal to boron is in the range from 0.5 to 4; D 0 to 5.0 wt% additives, different from A, B and C; wherein the sum of the components A to D is 100 wt% and wherein the moulding compound comprises neither copper halides nor metal phosphinates.

Abstract: A method (100) of generating and using one or more radiology analysis tools comprising: providing a labeling user interface (28, 40) on the workstation via which a user creates a labeled dataset by defining label types; receiving a user selection of desired output as at least one of the defined label types; identifying a proposed machine learning (ML) model based on the defined label types and the desired output; providing one or more GUI dialogs (40) presenting the proposed ML model and allowing the user to generate a user-designed proposed ML model (38) from the proposed ML model; training the user-designed ML model using training data comprising at least a portion of the labeled dataset, thereby generating a trained ML model (44); and deploying the trained ML model for an analysis process applied to at least a portion of radiology images and/or radiology reports in.

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: A non-transitory computer readable medium (26) stores instructions readable and executable by at least one electronic processor (20) to provide statistical analysis on one or more radiology databases (30, 32) in conjunction with a workstation (18) having a display device (24) and at least one user input device (22).

Abstract: The present disclosure relates to a method for configuring a medical device. The method comprises: providing a set of one or more parameters for configuring the medical device. Each parameter of the set has predefined values. A set of values of the set of parameters may be selected from the predefined values. Using the selected values the set of parameters may be set, which results in an operational configuration of the medical device. The medical device may be controlled to operate in accordance with the operational configuration, thereby an operating status of the medical device may be determined. Based on at least the operating status the operational configuration may be maintained or the selecting, setting and controlling may be repeatedly performed until a desired operating status of the medical device can be determined based on the operating statuses resulting from the controlling.

Abstract: A computer implemented method of making a measurement associated with a feature of interest in an image. The method comprises using (302) a model trained using a machine learning process to take the image as input and predict a pair of points between which to make the measurement of the feature of interest in the image. The method then comprises determining (304) the measurement, based on the predicted pair of points.

Abstract: An apparatus (1) for providing image quality feedback during a medical imaging examination includes at least one electronic processor (20) programmed to: receive a live video feed (17) of a display (6) of an imaging device controller (4) of an imaging device (2) performing the medical imaging examination; extract a preview image (12) from the live video feed; perform an image analysis (38) on the extracted preview image to determine whether the extracted preview image satisfies an alert criterion; and output an alert (30) when the extracted preview image satisfies the alert criterion as determined by the image analysis.

Abstract: Method for assessing a position of a patient with respect to an automatic exposure control chamber, AEC chamber (11, 12), for a medical exam, wherein a patient is positioned between an X-ray source and the AEC chamber (11, 12); comprising the steps:—acquiring (S10) an X-ray image (32) of at least part of the patient, wherein the AEC chamber is configured for detecting a radiation dose of the X-ray source;—determining (S20), by the control unit, a position of the AEC chamber (11, 12) with respect to the patient from the acquired X-ray image (32);—determining (S30), by the control unit, an exam protocol performed on the patient dependent on the medical exam to be performed on the patient and determining, by the control unit, an ideal position of the AEC chamber (11, 12) with respect to the patient dependent on the exam protocol, wherein the ideal position relates to a position of the patient relative to the AEC chamber (11, 12), in which the detected radiation dose is reliable for the medical exam; and—determin

Abstract: An apparatus (10) for manually auditing a set (30) of images having quality ratings (38) for an image quality metric assigned to the respective images of the set of images by an automatic quality assessment process (40) includes at least one electronic processor (20) programmed to: generate quality rating confidence values (42) indicative of confidence of the quality ratings for the respective images; select a subset (32) of the set of images for manual review based at least on the quality rating confidence values; and provide a user interface (UI) (27) via which only the subset of the set of images is presented and via which manual quality ratings (46) for the image quality metric are received for only the subset of the set of images.