Patent · US Active

Deep learning based processing of motion artifacts in magnetic resonance imaging data

US11320508B2 · kind B2 · utility

0Cited by

0References

15Claims

0Family size

Assignee

KONINIKLIJKE PHILIPS N.V. · NL

Inventors

Karsten Sommer · Hamburg, DE
TOM BROSCH · Hamburg, DE
TIM PHILIPP HARDER · Ahrensburg, DE
Jochen Keupp · Hamburg, DE
Ingmar Graesslin · Wenningstedt-Braderup (Sylt), DE
Rafael Wiemker · Kisdorf, DE
Axel Saalbach · Hamburg, DE

Key dates

Filing date	Oct 22, 2018
Grant date	May 3, 2022
Priority date	—
Expiry date	Oct 22, 2038

Classification

Technology area (CPC G)Physics
CPC primaryG06T2207/30168
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

The invention relates to a magnetic resonance imaging data processing system (126) for processing motion artifacts in magnetic resonance imaging data sets using a deep learning network (146, 502, 702) trained for the processing of motion artifacts in magnetic resonance imaging data sets. The magnetic resonance imaging data processing system (126) comprises a memory (134, 136) storing machine executable instructions (161, 164) and the trained deep learning network (146, 502, 702). Furthermore, the magnetic resonance imaging data processing system (126) comprises a processor (130) for controlling the magnetic resonance imaging data processing system. Execution of the machine executable instructions (161, 164) causes the processor (130) to control the magnetic resonance imaging data processing system (126) to: receive a magnetic resonance imaging data set (144, 500, 800), apply the received magnetic resonance imaging data set (144, 500, 800) as an input to the trained deep learning network (146, 502, 702), process one or more motion artifacts present in the received magnetic resonance imaging data set (144, 500, 800) using the trained deep learning network (146, 502, 702).

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.