Abstract: The present invention relates to peripheral perfusion measurement. In order to provide more detailed peripheral perfusion characteristics for better knowledge about a current situation, a device (10) for peripheral perfusion measurement is provided that comprises an image data input (12), a data processor (14) and an output interface (16). The image data input receives at least one perfusion angiographic 2D X-ray image of a region of interest of a subject's foot and a 3D foot-model comprising spatial perfusion-related parameters. The data processor registers the 3D foot-model with the foot in the at least one perfusion angiographic X-ray image. The registering comprises a pose-estimation of the foot in the 2D X-ray image. The information is mapped between the 2D image and the 3D foot-model based on the pose-estimation. Image processing modification instructions are identified based on the mapped information.

Abstract: A computer-implemented method for positioning a subject in medical imaging, comprising: receiving a first image (20) of a region of interest (14, 16) of the subject (S10); determining first positioning data based on the first image (20), wherein the first positioning data indicates an alignment of the region of interest (14, 16) relative to a first image acquisition unit used to acquire the first image (20) (S20); determining guidance data based on the first positioning data, wherein the guidance data comprises a guidance for an alignment of the region of interest (14, 16) relative to a second image acquisition unit used to acquire a second image (60) from a current alignment to a target alignment, wherein the target alignment is to correspond to that derived from the first positioning data (S30); providing the guidance data for acquiring the second image (60) (S40).

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: The present invention relates to an X-ray imaging system (10), comprising: an X-ray image acquisition unit (20); and a processing unit (30). The processing unit is configured to instruct the X-ray image acquisition unit to carry out a sequence of scans of a body part of a patient. The X-ray image acquisition unit is configured to provide the processing unit with an X-ray image of the body part for a scan of the sequence of scans. The processing unit is configured to determine that the scan needs to be repeated, wherein the determination comprises analysis of the X-ray image of the body part. The processing unit is configured to determine that an action other than acquisition of the next scan in the scan sequence is required, wherein the determination comprises analysis of the X-ray image of the body part.

Abstract: The disclosure relates to a system for analysis of medical image data, which represents a two-dimensional or three-dimensional medical image. The system is configured to read and/or determine, for the medical image, a plurality of image quality metrics and to determine a combined quality metrics based on the image quality metrics. The system is further configured so that the determination of the combined quality metrics takes into account an interaction between the image quality metrics in their combined effect on the combined quality metrics.

Abstract: The present invention relates to landmark and/or temporal event detection. It is proposed to utilize previously learned spatial statistical correlations between multiple landmarks in order to regularize convolutional neural networks (CNNs) either as a post-processing step or during training in order to utilize anatomical prior knowledge, reduce the false-positive prediction rate, and/or increase the accuracy and stability of the algorithm. The proposed apparatus and method may also be applied to improve the detection of correlated events in e.g., time-series by leveraging prior knowledge.

Abstract: The present invention relates to an apparatus (10) for determining an orientation of a patients chest. The apparatus comprises: an input unit (20); and a processing unit (30). The input unit is configured to receive an image of a patient, the image comprising image data of the patients chest. The input unit is configured to receive an X-ray radiograph of the patient's chest acquired by an X-ray imaging unit with an X-ray imaging axis extending from an X-ray source to an X-ray detector. The input unit is configured to provide the image and the X-ray radiograph to the processing unit. The processing unit is configured to determine an orientation of the patients chest in the X-ray radiograph with respect to the X-ray imaging axis, the determination comprising utilization of the image and the X-ray radiograph.

Abstract: An imaging system (SYS), comprising a medical imaging apparatus (IA). The medical imaging apparatus comprises a detector (D) for acquiring a first image of a patient in an imaging session, and a display unit (DD) for displaying the first image on a screen. The system further comprises, distinct from the medical imaging apparatus (IA), a mobile image processing device (MIP). The mobile processing device (MIP) comprises an interface (IN) for receiving a representation of the first image, and an image analyzer (IAZ) configured to analyze the representation and, based on the analysis, to compute, during the imaging session, medical decision support information. The decision support information is displayed on an on-board display device (MD) of the mobile processing device (MIP).