Siemens Healthcare Gmbh

Siemens Aktiengesellschaft

Siemens Healthineers Ag

Robert Lapp

Rainer Raupach

Ute Feuerlein

Christiane Koch

Stefan Kaepplinger

Michael Scheuering

Grzegorz Soza

Thomas Allmendinger

Martin Sedlmair

Christian Tietjen

Christoph Braun

Dieter Böing

Andreas Falkner

Andreas Prokein

Matthias Baer

Christian Blum

A computer-implemented method is for classifying a body type of at least one person. In an embodiment, the method includes receiving at least one image data record of the respective person, which maps at least one subarea of the person; and ascertaining a body type for the person by an optimization method. A respective person model is used for each of the possible body types, which as a function of at least one person parameter determines an expected person geometry of the person described by the person model. The body type is selected by the optimization method by a similarity measure for the similarity of the image data record or a person geometry ascertained from the image data record being optimized with the expected person geometry by selecting the body type.

Computer-implemented method for classifying a body type

A computer-implemented method is for comparing protocols. In an embodiment, the computer-implemented method includes first receipt of a first protocol relating to a performance of a measurement at a first medical device, including a plurality of first protocol steps; and second receipt of a second protocol relating to a performance of a measurement at a second medical device. The computer-implemented method further includes determination of a plurality of arrangements of the first protocol steps; determination of a plurality of comparison values, each of the comparison values being based on a comparison of the second protocol with one of the arrangements of the first protocol steps; determination of an agreement value based upon the plurality of comparison values; and provision of the agreement value.

Comparing protocols of medical imaging devices

A method is for checking a medical image with regard to a processing of the medical image via an image processing module. The method includes providing at least one input requirement of the image processing module relating to at least one image parameter of the medical image; providing the at least one image parameter of the medical image; and checking whether the at least one image parameter fulfills the at least one input requirement.

Method for checking a medical image and method for adapting an examination protocol during a medical imaging examination

A method and a system are disclosed for image acquisition, in which the protocol for controlling the CT scanner is computed automatically. The system includes a facility, which includes at least one CT scanner; a central PACS system in which image data and assigned metadata are stored as image data information, acquired with the facility; and an analysis unit, in terms of programming technology and/or circuit technology, for analyzing the captured image data information to automatically compute therefrom, the specific operating conditions and the facility-specific protocol parameters for the CT scanner protocol.

Method for computing a CT scanner protocol

A method and a system for monitoring a bolus value are disclosed. The method includes contrast-agent-assisted test recording of a time series of test images of a region under examination, wherein one bolus value is determined in each of the respective test images, together with the change in the bolus values between at least two test images. The method includes regulating the time interval between the recordings of individual test images as a function of the change in the bolus values, thereby enabling the temporal resolution for determining the bolus value to be selected in such a way that it corresponds to the change in the bolus values. In this way the temporal resolution in the monitoring of bolus values is improved with a view to avoiding both too high and too low a recording rate for the test images.

Dose- and time-optimized monitoring of bolus values

A method is disclosed for automatically selecting a scanning protocol for a tomographic recording of an X-ray image of a patient in that at least one patient-specific value is retrieved in the internal memory of a first computer. The patient-specific value can in particular be a measure of the anticipated X-ray absorption by the patient. The method includes automatically comparing the patient-specific value with retrievably stored reference values, wherein one scanning protocol can be associated with each reference value. Finally, a scanning protocol is automatically selected by way of the first computer using the comparison. Selection is simplified by automation of selection of the scanning protocol since no manual selection of the scanning protocol has to be made. Automatic selection of a suitable scanning protocol is also quicker than a manual selection.

Method and system for the automatic selection of a scanning protocol

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Nuremberg, Germany

Robert Lapp