During a medical intervention such as an angiography, the X-ray examination equipment (such as that mounted on a C-arm) produces a very large number of imaging frames of the intervention, as it progresses. This information contains frame sequences which can be effectively used to improve a medical report of the intervention. The sequence will contain sequences which contain similar clinical information though, and these frames may be considered to be redundant and not useful for inclusion in the medical report. The aspects detailed herein enable a selection of non-redundant sequences and/or frames, based on contextual information, obtained from the sequence of images, and/or other medical equipment, during an intervention. In this way, the redundancy inherent in the original frame sequence can be removed, leaving a set of prepared candidate sequences for insertion into a multimedia or documentary medical report.

The present disclosure provides systems and methods for performing quality control assessments of a three dimensional (3D) printing system. In particular, the present disclosure provides a phantom designs for use in 3D printing systems, as well as methods of quality control for a 3D printing system performed using a 3D printed phantom.

A computer system is configured to remove motion artifacts in medical images using a generative adversarial network (GAN). The computer system instantiates the GAN having one or more generative network(s) and one or more discriminative network(s) that are pitted against each other to train a generative model and a discriminative model. The training uses a training dataset including a plurality of medical images that are previously classified as without significant motion artifacts for diagnostic purposes. The discriminative model is trained to classify medical images as real or artificial. The generative model is trained to enhance the quality of a medical image and remove motion artifacts by producing a medical image directly from a post-contrast image, without using a pre-contrast mask.

The disclosure relates to systems and methods for evaluating a blood vessel. The method includes receiving image data of the blood vessel acquired by an image acquisition device, and predicting, by a processor, blood vessel condition parameters of the blood vessel by applying a deep learning model to the acquired image data of the blood vessel. The deep learning model maps a sequence of image patches on the blood vessel to blood vessel condition parameters on the blood vessel, where in the mapping the entire sequence of image patches contribute to the blood vessel condition parameters. The method further includes providing the blood vessel condition parameters of the blood vessel for evaluating the blood vessel.

A method and device are for automatic determination of the change of a hollow organ. The method includes providing a first medical image of the organ recorded at a first time; computing a first representation of the organ in the first image; computing a first reference-line of the organ based on the first representation and providing a second medical image of the organ recorded at a second point. The method further includes computing a second representation of the organ in the second image; computing a second reference-line of the organ based on the second representation of the organ; registering of the first and second reference-line to obtain at least one of matched representations of the organ and features derived from the matched representations of the organs; and comparing at least one of the matched representations of the organs and the features derived from the matched representations of the organ.

Embodiments of the present disclosure include a method, device and computer readable medium involving receiving image data of one or more coronary arteries, generating a binary segmentation indicating presence of calcium in the one or more coronary arteries from the image data, generating a branch density of the one or more coronary arteries, and assigning a coronary artery label from the branch density to the binary segmentation such that at least one indication of presence of calcium of the binary segmentation is labeled as present in a specific one of the one or more coronary arteries.

Systems and methods for detecting aortic aneurysms using ensemble based deep learning techniques that utilize numerous computed tomography (CT) scans collected from numerous de-identified patients in a database. The system includes software that automates the analysis of a series of CT scans as input (in DICOM file format) and provides output in two dimensions: (1) ranking CT scans by risks of adverse events from aortic aneurysm, (2) providing aortic aneurysm size estimates. A repository of CT scans may be used for training of deep neural networks and additional data may be drawn from localized patient information from institutions and hospitals which grant permission.

A system and method is provided for processing a positron emission tomography (PET) image of a subject having received a dose of a radiotracer that serves as chemical analog of an MC-I inhibitor. Specifically, the processing may includes identifying portions of the at least one PET image that represent MC-I expression levels.

For particularly quick and error-reduced navigation in vessel branches, a method is provided for visual support during navigation of a medical catheter introduced into a hollow organ system of a patient in a hollow organ branch, comprising the following steps: providing an, in particular pre-segmented, volume image of the hollow organ system and the hollow organ branch, which has been captured by means of an X-ray device; providing information relating to the geometric shape of the catheter tip; receiving a current projection image of the catheter tip, in particular by means of a cone beam X-ray device; registering the volume image and the projection image in the event that there is no pre-registration; determining the current position and current orientation of the catheter tip on the projection image based on the projection image; determining the relative position and relative orientation of the catheter tip in relation to the hollow organ branch; and displaying information relating to the determined relative position and/or relative orientation of the catheter tip in relation to the hollow organ branch.

Disclosed is a chest compression device. The chest compression device includes a back for supporting the back of a patient, a compression part for compressing the chest of the patient, a U-shaped support for supporting the compression part, a pair of driving parts for allowing the support and the compression part connected thereto to perform a vertical reciprocating movement, and a control part for controlling the operation of the pair of driving parts.