Patent · US Active

Motion artifact reduction of magnetic resonance images with an adversarial trained network

US10698063B2 · kind B2 · utility

7Cited by

1References

17Claims

0Family size

Assignee

Siemens Healthcare Limited · DE

Inventors

Sandro Braun · Karlsruhe, DE
Boris Mailhe · Plainsboro, US
Xiao Chen · Somerville, US
Benjamin L. Odry · West New York, US
Pascal Ceccaldi · New York, US
Mariappan S. Nadar · Plainsboro, US

Key dates

Filing date	Jun 14, 2018
Grant date	Jun 30, 2020
Priority date	—
Expiry date	Oct 19, 2038

Classification

Technology area (CPC G)Physics
CPC primaryG06T2207/20084
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

Systems and methods are provided for correcting motion artifacts in magnetic resonance images. An image-to-image neural network is used to generate motion corrected magnetic resonance data given motion corrupted magnetic resonance data. The image-to-image neural network is coupled within an adversarial network to help refine the generated magnetic resonance data. The adversarial network includes a generator network (the image-to-image neural network) and a discriminator network. The generator network is trained to minimize a loss function based on a Wasserstein distance when generating MR data. The discriminator network is trained to differentiate the motion corrected MR data from motion artifact free MR data.

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