Abstract: Systems and methods for automatically staging non-small cell lung cancer are provided. Patient data relating to a cancer of a patient is received. The patient data comprises one or more medical images and one or more biopsy reports. A T-stage of the cancer is determined based on a location and a size of one or more tumors of the cancer determined using the patient data. An N-stage of the cancer is determined by combining a metastasis evaluation of the cancer to regional lymph nodes determined from the one or more medical images and a metastasis evaluation of the cancer in the regional lymph nodes determined from the one or more biopsy reports. An M-stage of the cancer is determined based on a metastasis evaluation of the cancer to anatomical structures based on the patient data. The T-stage, the N-stage, and the M-stage are output.

Abstract: A method comprising: receiving 4D-tomographic image data, said 4D-tomographic image data including a plurality of 3D-tomographic image data of an examination object, and the plurality of 3D-tomographic image data corresponding to a plurality of time points; applying a segmentation algorithm to the 3D-tomographic image data, wherein the segmentation algorithm is configured to segment at least one organ in the 3D-tomographic image data to which the algorithm is applied; applying a scoring function to the segmented organ(s), wherein the scoring function is configured to determine a scoring value(s) for the segmented organ(s), and wherein the scoring value includes and/or corresponds to a metric quantifying an extent to which a vicinity of voxels at a surface of the segmented organ(s) contain(s) an image artifact; comparing the scoring value(s) with a threshold value; and providing a user notification, when at least one scoring value exceeds the threshold value.

Abstract: A wearable device worn by a user is disclosed which includes a plurality of input device interfaces each configured to receive input from a sensor coupled to a user, a controller configured to generate a two-dimensional map of the user's three-dimensional space based on the received inputs, and a plurality of haptic feedback devices disposed on the wearable device, wherein the controller is configured to selectively activate each of the plurality of haptic feedback devices to signal the user's position in the three-dimensional space based on the generated two-dimensional map as the user moves in the three-dimensional space.

Abstract: A computer-implemented method and a corresponding apparatus are provided for the provision of a two-dimensional visualization image having a plurality of visualization pixels for the visualization of a three-dimensional object represented by volume data for a user. Context information for the visualization is obtained by the evaluation of natural language and is taken into account in the visualization. The natural language can be in the form of electronic documents, which are assigned or can be assigned to the visualization process. In addition, the natural language can be in the form of a speech input of a user, during or after the visualization.

Abstract: Risks of radiation-induced toxicity associated with a radiotherapy treatment of a target region of a patient are predicted. Data associated with a region of interest comprising the target region is received. The received data includes a predefined dose map of the radiotherapy treatment and pre-radiotherapy-treatment imaging data of the region of interest. A trained machine-learning algorithm is applied to the received data. The trained machine-learning algorithm generates at least one toxicity indicator based on the received data. The at least one toxicity indicator is indicative of the risks of the radiation-induced toxicity.

Abstract: Systems and methods for automatically staging non-small cell lung cancer are provided. Patient data relating to a cancer of a patient is received. The patient data comprises one or more medical images and one or more biopsy reports. A T-stage of the cancer is determined based on a location and a size of one or more tumors of the cancer determined using the patient data. An N-stage of the cancer is determined by combining a metastasis evaluation of the cancer to regional lymph nodes determined from the one or more medical images and a metastasis evaluation of the cancer in the regional lymph nodes determined from the one or more biopsy reports. An M-stage of the cancer is determined based on a metastasis evaluation of the cancer to anatomical structures based on the patient data. The T-stage, the N-stage, and the M-stage are output.

Abstract: Risks of radiation-induced toxicity associated with a radiotherapy treatment of a target region of a patient are predicted. Data associated with a region of interest comprising the target region is received. The received data includes a predefined dose map of the radiotherapy treatment and pre-radiotherapy-treatment imaging data of the region of interest. A trained machine-learning algorithm is applied to the received data. The trained machine-learning algorithm generates at least one toxicity indicator based on the received data. The at least one toxicity indicator is indicative of the risks of the radiation-induced toxicity.

Abstract: A computer-implemented method and a corresponding apparatus are provided for the provision of a two-dimensional visualization image having a plurality of visualization pixels for the visualization of a three-dimensional object represented by volume data for a user. Context information for the visualization is obtained by the evaluation of natural language and is taken into account in the visualization. The natural language can be in the form of electronic documents, which are assigned or can be assigned to the visualization process. In addition, the natural language can be in the form of a speech input of a user, during or after the visualization.

Abstract: A method is for positioning a positionable table for a patient inside a medical imaging device. In an embodiment, the method includes a determination of a table position as a function of an organ or body part of the patient for examination; an ascertainment of correction data for correcting the table position; a determination of a corrected table position based on the ascertained correction data; and a positioning of the table at the corrected table position.

Abstract: The present invention relates to a method and system for separating CO2 based on regenerative chemical absorption, including an absorber where the CO2 remains retained in an absorbent liquid, and including a regenerator where the CO2 is released, obtaining a regenerated absorbent that is re-used in the absorption unit. The invention proposes a configuration of the entire capturing process which allows an efficient operation that significantly reduces the energy requirements mainly associated with the regeneration of the absorbent, as well as a lesser thermal degradation of same.

Abstract: A method and system for non-invasive assessment of coronary artery stenosis is disclosed. Patient-specific anatomical measurements of the coronary arteries are extracted from medical image data of a patient acquired during rest state. Patient-specific rest state boundary conditions of a model of coronary circulation representing the coronary arteries are calculated based on the patient-specific anatomical measurements and non-invasive clinical measurements of the patient at rest. Patient-specific rest state boundary conditions of the model of coronary circulation representing the coronary arteries are calculated based on the patient-specific anatomical measurements and non-invasive clinical measurements of the patient at rest. Hyperemic blood flow and pressure across at least one stenosis region of the coronary arteries are simulated using the model of coronary circulation and the patient-specific hyperemic boundary conditions.

Abstract: A method and system for non-invasive assessment of coronary artery stenosis is disclosed. Patient-specific anatomical measurements of the coronary arteries are extracted from medical image data of a patient acquired during rest state. Patient-specific rest state boundary conditions of a model of coronary circulation representing the coronary arteries are calculated based on the patient-specific anatomical measurements and non-invasive clinical measurements of the patient at rest. Patient-specific rest state boundary conditions of the model of coronary circulation representing the coronary arteries are calculated based on the patient-specific anatomical measurements and non-invasive clinical measurements of the patient at rest. Hyperemic blood flow and pressure across at least one stenosis region of the coronary arteries are simulated using the model of coronary circulation and the patient-specific hyperemic boundary conditions.

Abstract: A method and system for dose-optimized acquisition of a computed tomography (CT) scan of a target organ is disclosed. A localizer spiral CT scan is started at a beginning of a confidence range before a target organ. Real-time localizer scan images are automatically analyzed to predict a beginning location of the target organ based on the real-time localizer scan images. A diagnostic spiral CT scan is automatically started at the predicted beginning location of the target organ. Real-time diagnostic scan images are automatically analyzed to predict an end location of the target organ where full coverage of the target organ will be reached. The diagnostic spiral CT scan is automatically stopped in response to reaching the predicted end location of the target organ. A 3D profile can be acquired using a 3D camera and used to determine the confidence range before the target organ.

Abstract: A method and system for dose-optimized acquisition of a computed tomography (CT) scan of a target organ is disclosed. A localizer spiral CT scan is started at a beginning of a confidence range before a target organ. Real-time localizer scan images are automatically analyzed to predict a beginning location of the target organ based on the real-time localizer scan images. A diagnostic spiral CT scan is automatically started at the predicted beginning location of the target organ. Real-time diagnostic scan images are automatically analyzed to predict an end location of the target organ where full coverage of the target organ will be reached. The diagnostic spiral CT scan is automatically stopped in response to reaching the predicted end location of the target organ. A 3D profile can be acquired using a 3D camera and used to determine the confidence range before the target organ.

Abstract: An embodiment of the invention relates to a system. In an embodiment, the system includes a component of a medical imaging apparatus; a mobile control device including an operating element designed as an electromechanical switching element; and a control unit designed to output a control signal to the component. When the system is in an operating state, the mobile control device and the control unit are coupled such that an actuation of the operating element causes the control signal to be output to the component via the control unit.

Abstract: A method is for positioning a positionable table for a patient inside a medical imaging device. In an embodiment, the method includes a determination of a table position as a function of an organ or body part of the patient for examination; an ascertainment of correction data for correcting the table position; a determination of a corrected table position based on the ascertained correction data; and a positioning of the table at the corrected table position.

Abstract: A method and system for automatic coronary stenosis detection in computed tomography (CT) data is disclosed. Coronary artery centerlines are obtained in an input cardiac CT volume. A trained classifier, such as a probabilistic boosting tree (PBT) classifier, is used to detect stenosis regions along the centerlines in the input cardiac CT volume. The classifier classifies each of the control points that define the coronary artery centerlines as a stenosis point or a non-stenosis point.

Abstract: A method and system for automatic aortic valve calcification evaluation is disclosed. A patient-specific aortic valve model in a 3D medical image volume, such as a 3D computed tomography (CT) volume. Calcifications in a region of the 3D medical image volume defined based on the aortic valve model. A 2D calcification plot is generated that shows locations of the segmented calcifications relative to aortic valve leaflets of the patient-specific aortic valve model. The 2D calcification plot can be used for assessing the suitability of a patient for a Transcatheter Aortic Valve Replacement (TAVI) procedure, as well as risk assessment, positioning of an aortic valve implant, and selection of a type of aortic valve implant.

Abstract: A device is disclosed for determining and visualizing the perfusion of the myocardial muscle with the aid of static CCTA images. In at least one embodiment, the device includes a segmentation unit for segmenting the coronary blood vessels and the left myocardial muscle from a CCTA image of the heart; a first simulation unit for simulating the blood flow through the coronary blood vessels; and a second simulation unit by which the local perfusion of the myocardial muscle is determined on the basis of the ascertained blood flow into different regions of the myocardial muscle. The perfusion of the different regions of the myocardial muscle is visualized in a schematized image on a visualization unit. By virtue of the proposed device it is possible to dispense with further imaging examinations after the performance of a CCTA scan, thereby relieving the pressure both on the part of the physician and on the part of the patient.

Abstract: A method and system for extracting coronary artery centerlines from 3D medical image volumes is disclosed. Heart chambers are segmented in a 3D volume. Coronary artery centerlines are initialized in the 3D volume coronary artery based on the segmented heart chambers. The coronary artery centerlines are locally refined based on a vesselness measure. A length of each coronary artery centerline is shrunk to verify that the coronary artery centerline is within a coronary artery. The coronary artery centerline is the extended using data-driven vessel tracing.