Siemens Healthineers Ag

Siemens Healthcare Gmbh

Oliver Taubmann

Michael Suehling

Alexander Muehlberg

Hendrik Ditt

Felix Lades

Felix Durlak

Rainer Kaergel

Michael Wels

Michael Sühling

Alexander Katzmann

Florian Thamm

Leonhard Rist

Felix Denzinger

Matthias May

Wladimir Lesyuk

Michael Uder

Alexander Mühlberg

One or more example embodiments of the invention relates in one aspect to a computer-implemented method for providing a stroke information. The method includes receiving examination data, the examination data comprising computed tomography imaging data of an examination area of a patient, the examination area of the patient comprising at least one brain region, the at least one brain region being affected by a stroke; adjusting a causal model based on the computed tomography imaging data to obtain an adjusted causal model, wherein the adjusted causal model models a first variable as a first cause for an appearance of the examination area of the patient; receiving a first value for the first variable; generating the stroke information based on the adjusted causal model and the first value for the first variable; and providing the stroke information.

Method and data processing system for providing a stroke information

A computer implemented method maps a three-dimensional branched tubular structure depicted in a three-dimensional image data set into at least one two-dimensional image plane.

Method, device and computer-readable medium for mapping a three-dimensional branched tubular structure into at least one two-dimensional image plane

A computer-implemented method and system are for parametrizing a function including a processing algorithm and a representation generator, the representation generator being designed to generate at least one representation. In an embodiment, the method includes using an optimization algorithm to determine the processing algorithm and the at least one representation parametrization. The optimization algorithm optimizes a measure for the performance of the processing algorithm when operating on a set of training representations generated by applying the representation generator to training medical image datasets, by varying on the one hand the content of the at least one representation parametrization and/or the number of used representation parametrizations and on the other hand the processing algorithm and the algorithm parameters.

Computer-implemented method for parametrizing a function for evaluating a medical image dataset

At least one example embodiment relates to a computer-implemented method for providing stroke information, the method comprising

A computer-implemented method is for providing a clinical information. In an embodiment, the computer-implemented method includes receiving input data including a graph representation of a plurality of disease lesions of a patient; applying a trained function to the input data to generate the clinical information, the trained function being based on a graph machine learning model; and providing the clinical information, the clinical information including at least one information for prediction of the disease progression, survival or therapy response of the patient.

Method for obtaining disease-related clinical information

A computer-implemented method is for providing radiomics-related information. In an embodiment, the computer-implemented method includes receiving radiomics-related data; determining, based on the radiomics-related data and an assistance algorithm, a function for processing the radiomics-related data; calculating, based on the radiomics-related data and the function for processing the radiomics-related data, the radiomics-related information; and providing the radiomics-related information.

Method and data processing system for providing explanatory radiomics-related information

A method for operating a medical imaging apparatus includes acquiring a first image data set of a region of interest of the patient; automatically evaluating the first image data set using at least one evaluation algorithm yielding evaluation information, regarding at least one type of findings, describing a presence of at least one finding of the type requiring the acquisition of a second image data set and at least one imaging parameter for the second image data set; automatically notifying a user, upon the evaluation information indicating the presence of a required second image data set, of the required acquisition of the second image data set; and acquiring the second image data set acquiring the second image data set after confirmation of acquisition of the second image data set by the user, in a same examination process, using the at least one imaging parameter of the evaluation information.

Growing community of inventors

Weilersbach, Germany

Oliver Taubmann