Siemens Healthcare Gmbh

Semikron Elektronik Gmbh &co.kg

Siemens Healthineers Ag

Martin Kraus

Mehmet Akif Gulsun

Andre Aichert

Birgi Tamersoy

Arnaud Arindra Adiyoso

Florin-Cristian Ghesu

Tobias Heimann

Marvin Teichmann

Klaus Benkert

André Aichert

A computer-implemented method includes receiving first medical image data, wherein the first medical image data is based on a first medical imaging of an examination object, receiving second medical image data, wherein the second medical image data is based on a second medical imaging of the examination object, wherein the first and the second medical imaging differ by at least one of an imaging modality or by an imaging protocol used, wherein the first and the second medical image data are registered with one another, determining synthetic image data by applying a trainable function to the first medical image data, determining a measure of similarity with a similarity function by comparison of the synthetic image data and the second medical image data, adjusting at least one parameter of the trainable function by optimization of the similarity function based on the measure of similarity, provision of the trainable function.

Method for providing a trainable function for determination of synthetic image data

A functional component and having a partial plastic housing element with a plastic housing wall, the plastic housing wall having a device identification region integrated into the plastic housing wall and thus realizing a constituent part of the plastic housing wall. The device identification region comprising identification elements integrated into the plastic housing wall, those identification elements that realize part of a surface of the plastic housing wall realizing device identification elements, the device identification region being realized individually for the device by the device identification elements, such that the device can be unambiguously identified by means of the device identification region.

Device having functional component and a plastic housing element, and method for verifying the authenticity of such a device

A meta-learning system includes an inner function computation module, adapted to compute output data from applied input data according to an inner model function, depending on model parameters; an error computation module, adapted to compute errors indicating mismatches between the computed output data and target values; a state update module, adapted to update the model parameters of the inner model function according to an updated state, updated based on a current state of the state update module, in response to an error received from the error computation module. The state update module is learned to adjust the model parameters of the inner model function, such that a following training of the inner model function with training data is improved.

Meta-learning system

A method and a system are for performing at least one inference task on medical input data. In an embodiment, the system includes: a computing device configured to implement an artificial neural network, ANN. The ANN is configured to receive medical input data as an input and to perform at least one inference task based on the medical input data. The ANN includes an output layer with, for at least one inference task of the at least one inference task, a plurality of output nodes. Each output node corresponds to one quantile out of a plurality of defined quantiles.

Method for learning from data with label noise

Various example embodiments pertain to processing images that depict tissue samples using a neural network algorithm. The neural network algorithm includes multiple encoder branches that are copies of each other that share the same parameters. The encoder branches can, accordingly, be referred to as Siamese copies of each other.

Digital pathology using an artificial neural network

A power semiconductor module has a first and second intermediate circuit rail, an AC potential rail and with a packaged first and second power semiconductor switch. The respective power semiconductor switch has a first and second load current terminal and a control terminal, wherein the first power semiconductor switch is between the first intermediate circuit rail and the AC potential rail and the second power semiconductor switch is between the second intermediate circuit rail and the AC potential rail. The first load terminal of the first power semiconductor switch is contacted to the first intermediate circuit rail and the second load terminal of the first power semiconductor switch is electrically conductively contacted to the AC potential rail.

Power semiconductor module with power semiconductor switches

A system and a method are provided for a parameter update. In an embodiment, the method includes obtaining, by a first entity, a function and parameter data from a second entity; selecting data samples provided by the first entities; providing a plurality of mutually isolated computing instances; assigning and providing the selected data samples to the computing instances; calculating, within each computing instance, results of the function; calculating averages over the results; determining whether the function fulfils a security criterion, and, if so: providing the calculated average for the gradient of the loss function and/or the calculated average of the output value and/or updated parameter data to the second entity.

Growing community of inventors

Fuerth, Germany

Martin Kraus