Siemens Healthineers Ag

Siemens Healthcare Gmbh

Andreas Prokein

Rainer Raupach

Vivek Kumar Singh

Ankur Kapoor

Andreas Wimmer

Robert Lapp

Brian Teixeira

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

CT scan parameters for performing a CT scan of an anatomical target region of a patient are determined and/or adjusted. An initial set of the CT scan parameters for starting to perform the CT scan is determined based on an initial set of attenuation curves associated with the anatomical target region of the patient. The initial set of attenuation curves are determined based on optical imaging data depicting the patient.

Determining CT scan parameters based on machine learning

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Bubenreuth, Germany

Andreas Prokein