Siemens Healthineers Ag

Michael Bush

Mariappan S Nadar

Boris Mailhe

Simon Arberet

Vibhas S Deshpande

Thomas Benkert

Kelvin Chow

Laszlo Lazar

Nirmal Janardhanan

For imaging an object subject to a cyclic motion, two or more imaging repetitions are carried out. Each of the imaging repetitions includes a sequence of equally spaced imaging events, wherein each imaging event has an event number, which corresponds to a respective predefined imaging parameter. A cycle duration of the cyclic motion is determined, a number of events per cycle is determined based on the cycle duration and a shift number is determined at least in part randomly. For a first imaging repetition, a starting number is determined depending on the number of events per cycle and the shift number. The first imaging repetition is carried out, wherein the respective sequence is started with an imaging event, whose event number is given by the starting number.

Imaging an object subjected to a cyclic motion

For magnetic resonance (MR) reconstruction using artificial intelligence (AI), the AI-based reconstruction for MR imaging systems is offloaded to one or more servers. A remote server performs AI-based reconstruction. A library of recent, old, custom, and/or publicly available AI-based reconstruction processes may be rapidly deployed and available to the server, which has the memory and processing resources for AI-based reconstruction. Load balancing of the data and/or between servers may improve performance.

Architecture for artificial intelligence-based magnetic resonance reconstruction

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Brooklyn, NY, United States of America

Michael Bush