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: In order to enhance enhanced X-ray image inhalation quality monitoring, a metric is proposed hat reproducibly provides an index of ribs visible to be used in the assessment of the inhalation state. In an example, a detected diaphragm in a chest X-ray image may be projected into an atlas that contains labels for all intercostal spaces, namely spaces between rib centerlines. A spatial representation of both the clavicle and the ribs is provided in the atlas, a cumulative histogram is built for all points, i.e. pixels, of the diaphragm, for every point a rib label counter of the rib in the rib label map at that point is incremented as well as all ribs above it, the rib label counter is normalized by a division by the number of points, the median (or a different quantile) may be taken of this distribution serving as an inhalation index. An objective metric of inhalation state is thus achieved.

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: 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 invention relates to a method (100) for supervised training of an artificial neural network for medical image analysis. The method comprises acquiring (SI) first and second sets of training samples, wherein the training samples comprise feature vectors and associated predetermined labels, the feature vectors being indicative of medical images and the labels pertaining to anatomy detection, to semantic segmentation of medical images, to classification of medical images, to computer-aided diagnosis, to detection and/or localization of biomarkers or to quality assessment of medical images. The accuracy of predetermined labels may be better for the second set of training samples than for the first set of training samples. The neural network is trained (S3) by reducing a cost function, which comprises a first and a second part.

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: 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: A system (SYS) for supporting a medical procedure, comprising an interface (IN) for receiving at least one medical input signal that describes a state of a target anatomy. A signal analyzer (SA) is configured to analyze the medical input signal to determine a time window for deployment of a cardio-vascular device (CL) to be deployed by a deployment.