Siemens Healthcare Gmbh

Siemens Healthineers Ag

Heinrich Von Busch

Robert Grimm

Berthold Kiefer

Dorin Comaniciu

Ali Kamen

Bin Lou

Mamadou Diallo

David Jean Winkel

Tongbai Meng

Xin Yu

Bibo Shi

Nicolas Von Roden

Sasa Grbic

Zhoubing Xu

Volker Matschl

Thomas Pheiffer

Rainer Kurth

Ahmet Tuysuzoglu

Guillaume Chabin

Andre Bender

Daniel Gareis

Manuel Noras

Ioan Marius Popdan

Alin Madalin Draghia

Manasi Datar

Kareem Abdelrahman

Matteo Barbieri

Systems and methods are provided for optimizing a deep learning model. A multi-site dataset associated with different clinical sites and a deployment dataset associated with a deployment clinical site are received. A deep learning model is trained based on the multi-site dataset. The trained deep learning model is optimized based on the deployment dataset. The optimized trained deep learning model is output.

Localization and classification of abnormalities in medical images

Systems and methods for performing an assessment of a lesion are provided. A plurality of input medical images of a lesion is received. The plurality of input medical images comprises an initial input medical image and one or more additional input medical images. The initial input medical image comprises a region of interest around the lesion. A mask of the lesion is curated for the initial input medical image based on the region of interest and a set of candidate masks. The region of interest in the initial input medical image is propagated to the one or more additional input medical images based on prior registration transformations. A mask of the lesion is curated for each of the one or more additional input medical images based on the propagated regions of interest and the set of candidate masks. One or more assessments of the lesion are performed based on the mask for the initial input medical image, the masks for the one or more additional input medical images, and prior assessments of lesions. Results of the one or more assessments of the lesion are output.

AI driven longitudinal liver focal lesion analysis

In a method for an actuation of a magnetic resonance device for capturing image data from an examination region of an examination object, at least one first control sequence is provisioned, the magnetic resonance device is actuated according to the at least one first control sequence to capture first data from the examination object, the first data is analyzed with respect to a property to generate a result, and, based on the result, a selective performance of one of: a selection of a further control sequence, and termination of the actuation of the magnetic resonance device, is performed.

Method for an adaptive actuation of a magnetic resonance device

In a method for generating a surrogate marker based on medical image data mapping an image region, the medical image data is detected using a first interface, a first subregion of the image region is selected by segmenting a first structure included in the image region, a first property of the first subregion is extracted, the surrogate marker is determined based on the first property, and the surrogate marker is provided using a second interface.

Methods and systems for generating surrogate marker based on medical image data

Systems and methods are provided for classifying an abnormality in a medical image. An input medical image depicting a lesion is received. The lesion is localized in the input medical image using a trained localization network to generate a localization map. The lesion is classified based on the input medical image and the localization map using a trained classification network. The classification of the lesion is output. The trained localization network and the trained classification network are jointly trained.

The present embodiments relate to an MR local coil arrangement and an MR unit. An MR local coil arrangement is disclosed including at least one MR antenna, an illumination unit with at least one light-generating unit to illuminate an illumination region, and a switching unit with at least one sensor to control the illumination unit.

Illuminated MR local coil arrangement

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Uttenreuth, Germany

Heinrich Von Busch