Siemens Healthineers Ag

Peter Gall

Atilla Peter Kiraly

René Kartmann

Benedikt Krüger

Jens Gühring

Lars Lauer

Christoph Forman

Uvo Hölscher

Techniques are described for providing image-based operational decision support. The technique includes using a decision engine configured to generate output data based on a determined number of clinical findings in medical images of a patient. The decision module is configured to generate decision data depending on position data defining an actual position of the patient in a predefined clinical guideline, which comprises a set of possible next steps subsequent to the actual position. The decision data comprises information indicating which next steps from the set of possible next steps of the clinical guideline should be performed. The disclosure further describes a related method, a clinical decision system, and a related medical imaging system.

Decision module and method for image-based operational decision support

Techniques are described for providing image-based operational decision support. The technique includes providing initial imaging data from a preceding examination of a patient, determining clinical findings by automated processing of the initial imaging data, generating decision data at least comprising a decision whether a further recording of a number of images is necessary, and generating a suggested set of imaging parameter values for recording this number of images. The decision data may be based on the determined clinical findings, and the technique may further include outputting the suggested set of imaging parameter values for recording a number of images of the patient. Also described are a related clinical decision system, a decision module, and a related medical imaging system.

Method and system for image-based operational decision support

A magnetic resonance (MR) system compensation interface having: a hardware subinterface configured to receive individual hardware parameters from an individual scan unit of an MR system; a model determination unit configured to determine an imperfection model on the basis of the hardware parameters; a compensation model determination unit configured to determine a compensation model on the basis of the imperfection model; an application subinterface configured to receive application data assigned to an application; and a compensation unit configured to determine compensated application data on the basis of the received application data and the determined compensation model.

Compensation interface for a magnetic resonance imaging system

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Uttenreuth, Germany

Peter Gall