Siemens Healthcare Gmbh

Siemens Healthineers Ag

Other

Siemens Medical Solutions Usa, Inc.

Siemens Healthcare Diagnostics Gmbh

Dominik Neumann

Dorin Comaniciu

Bogdan Georgescu

Tommaso Mansi

Shaohua Kevin Zhou

Sasa Grbic

Puneet Sharma

Yefeng Zheng

Ali Kamen

Tiziano Passerini

Lucian Mihai Itu

Wen Hong Liu

Zhoubing Xu

Ingmar Voigt

Chris Schwemmer

Eugen Kubala

Saikiran Rapaka

Mehmet Akif Gulsun

Viorel Mihalef

Florin Cristian Ghesu

Ulrich Hartung

Ruth J Soenius

Oliver Frings

Razvan Ionasec

Helene C Houle

Max Schoebinger

Julian Krebs

Siqi Liu

Jan Kretschmer

Bruce S Spottiswoode

Olivier Ecabert

Andrzej Milkowski

Jonathan Sperl

Serkan Cimen

Rainer Kaergel

Max Schöbinger

Günther Platsch

Guillaume Chabin

Anamaria Vizitiu

Awais Mansoor

Carsten Dietrich

Puyang Wang

Fei Gao

Maximilian Würstle

Vlad Comanelea-Serban

Joel Mancina

Maximilian Weiss

Maximilian Wuerstle

Rainer Kärgel

Mallory Selzo

Anna Boehm

Martin Von Roden

Olivier Pauly

Anna Böhm

Angiography angles are determined. Patient information and target vessel information are obtained, wherein the patient information defines individual medical information of a patient and wherein the target vessel information defines at least one target vessel to be imaged. At least one angiography angle is determined based on the patient information and the target vessel information. Angiograms obtained using the at least one angiography angle are analyzed to determine a vessel coverage of the target vessel and based on the vessel coverage determines additional angiography angles.

Method and system for improved vessel coverage from angiography

A computer-implemented method is for providing quantitative airway information. In an embodiment, the method includes receiving and/or determining first medical image data of an airway segment; applying a first trained function to the first medical image data, to generate output data; determining the at least one quantitative airway information of the airway segment based on the output data; and providing the at least one quantitative airway information.

Method for providing airway information

For robust view classification and measurement estimation in sequential ultrasound imaging, the classification and/or measurements for a given image or sequence of images are gated. To prevent oscillation in results, the gating provides consistent output.

Robust view classification and measurement in ultrasound imaging

The invention describes a method for automatically localizing organ segments in a three-dimensional image comprising the following steps: providing a three-dimensional image showing at least one organ and at least one tubular network comprising a plurality of tubular structures, the organ comprising organ segments; performing automatic separation of the organ from other parts of the image; performing automatic tracing of the tubular network to obtain a branch map; performing automatic analysis of the branch map to identify specific tubular structures; performing automatically assigning regions of the organ to the specific tubular structures to segment the organ into localized organ segments; and outputting the localized organ segments and the traced and analyzed tubular network as image data. The invention further describes a localization arrangement and a medical imaging system.

Method and arrangement for automatically localizing organ segments in a three-dimensional image

One or more example embodiments of the present invention relates to a method for the automated determination of examination results in an image sequence from multiple chronologically consecutive frames, the method comprising determining diagnostic candidates in the form of contiguous image regions in the individual frames for a predefined diagnostic finding; and for a number of the diagnostic candidates, determining which candidate image regions in other frames correspond to the particular diagnostic candidate, determining whether the candidate image regions of the particular diagnostic candidate in the other frames overlap with other diagnostic candidates, generating a graph containing the determined diagnostic candidates of the frames as nodes and the determined overlaps as edges, and generating communities from nodes connected via edges.

Method and system for the automated determination of examination results in an image sequence

A method for providing a secondary parameter, a decision support system, a computer-readable medium and a computer program product are disclosed. In an embodiment, the method is for providing a secondary parameter in a decision support system providing a primary parameter, in particular in a clinical decision support system. The method includes: providing an input data set; approximating a secondary parameter based on the input data set by using a sub-system being trained by a machine learning mechanism, in particular by a deep learning mechanism; and providing the approximated secondary parameter. The input data set is a shape data set.

Method for providing a secondary parameter, decision support system, computer-readable medium and computer program product

A system is for infectious disease notification. The system includes at least one processor, configured to use a machine learning monitoring algorithm, trained on a large number of EMR datasets of patients, to calculate a probability for an infectious disease from a provided EMR dataset and compare the probability of the provided EMR dataset calculated with a known value. In training of the monitoring algorithm, the value represents whether there was an onset of an infectious disease or not and the monitoring algorithm is designed to adjust parameters of the monitoring algorithm. And in evaluating a notification, the value is a threshold value and the system is designed to output a notification upon the probability being greater than the threshold value.

System and method for infectious disease notification

A method and a device are for exchanging information regarding the clinical implications genomic variations. In an embodiment, the method includes receiving login-data of a user; evaluating the login-data received; establishing an encrypted data connection to the user after the evaluating indicates a positive evaluation of the login-data; saving, upon receiving a dataset in a context of a genomic variation, the dataset received in a memory, context-related with the genomic variation; and evaluating, upon a user request being received and connected with a search query for the genomic variation, a set of datasets from the memory, the datasets being context-related with the genomic variation and the set including the datasets that the user is authorized to receive, and sending the set of datasets to the user.

Method and device for exchanging information regarding the clinical implications of genomic variations

Intelligent multi-scale image parsing determines the optimal size of each observation by an artificial agent at a given point in time while searching for the anatomical landmark. The artificial agent begins searching image data with a coarse field-of-view and iteratively decreases the field-of-view to locate the anatomical landmark. After searching at a coarse field-of view, the artificial agent increases resolution to a finer field-of-view to analyze context and appearance factors to converge on the anatomical landmark. The artificial agent determines applicable context and appearance factors at each effective scale.

Intelligent multi-scale medical image landmark detection

A method of generating a first image from a medical text report comprises acquiring a medical text report comprising one or more natural language statements; analysing the medical text report, using a computer-implemented analysis process, to determine for each natural language statement whether the statement satisfies a predetermined criterion with respect to a first medical finding; and responsive to a determination that a said statement satisfies the predetermined criterion, adding an image representing the first medical finding to an image template, to generate the first image. Also disclosed is an apparatus and computer program.

Image generation from a medical text report

Systems and methods are provided for evaluating an aorta of a patient. A medical image of an aorta of a patient is received. The aorta is segmented from the medical image. One or more measurement planes are identified on the segmented aorta. At least one measurement is calculated at each of the one or more measurement planes. The aorta of the patient is evaluated based on the at least one measurement calculated at each of the one or more measurement planes.

Automatic detection and quantification of the aorta from medical images

An embodiment of a method includes providing a first result list indicating a plurality of first anatomic structures and indicating, for each respective first anatomic structure of the plurality of first anatomic structures, a corresponding first severity indicator; providing a second result list indicating, for each respective second anatomic structure of the plurality of the second anatomic structures, a corresponding second severity indicator; providing a relationship matrix indicating a level of interrelatedness between the first anatomic structures and the second anatomic structures; and generating, based on the first result list provided, on the second result list and on the relationship matrix provided, a concordance visualization indicating a respective level of concordance between at least one of the first anatomic structures and the corresponding first severity indicator, and indicating a respective level of concordance between at least one of the second anatomic structures and the corresponding second severity indicator.

Automatically generating synchronized view and level of concordance of diagnostic exams

A method and system for estimating physiological heart measurements from medical images and clinical data disclosed. A patient-specific anatomical model of the heart is generated from medical image data of the patient. A patient-specific multi-physics computational heart model is generated based on the patient-specific anatomical model by personalizing parameters of a cardiac electrophysiology model, a cardiac biomechanics model, and a cardiac hemodynamics model based on medical image data and clinical measurements of the patient. Cardiac function of the patient is simulated using the patient-specific multi-physics computational heart model. The parameters can be personalized by inverse problem algorithms based on forward model simulations or the parameters can be personalized using a machine-learning based statistical model.

Systems and methods for estimating physiological heart measurements from medical images and clinical data

A method and system for estimating tissue parameters of a computational model of organ function and their uncertainty due to model assumptions, data noise and optimization limitations is disclosed. As applied to a cardiac use-case, a patient-specific anatomical heart model is generated from medical image data of a patient. A patient-specific computational heart model is generated based on the patient-specific anatomical heart model. Patient-specific parameters and corresponding uncertainty values are estimated for at least a subset of parameters of the patient-specific computational heart model. A surrogate model is estimated for a forward model of cardiac function, and the surrogate model is applied within Bayesian inference to estimate the posterior probability density function of the parameter space of the forward model. Cardiac function for the patient is simulated using the patient-specific computational heart model. The estimated parameters, their uncertainty, and the computed cardiac function are displayed to the user.

Method and system for image-based estimation of multi-physics parameters and their uncertainty for patient-specific simulation of organ function

Growing community of inventors

Erlangen, Germany

Dominik Neumann