Patent · US Active

Low rank and spatial regularization model for magnetic resonance fingerprinting

US10866298B2 · kind B2 · utility

0Cited by

1References

9Claims

0Family size

Assignee

Siemens Healthcare Limited · DE

Inventors

Simon Arberet · Princeton, US
Xiao Chen · Somerville, US
Boris Mailhe · Plainsboro, US
Mariappan S. Nadar · Plainsboro, US
Peter Speier · Erlangen, DE

Key dates

Filing date	Jul 25, 2018
Grant date	Dec 15, 2020
Priority date	—
Expiry date	Dec 25, 2038

Classification

Technology area (CPC G)Physics
CPC primaryG06F18/2135
WIPO fieldMeasurement
WIPO sectorInstruments

Abstract

Systems and methods are provided for iterative reconstruction of a magnetic resonance image using Magnetic Resonance Fingerprinting (MRF). An image series is estimated according to the following three steps: a gradient step to improve data consistency, fingerprint matching, and a spatial regularization. Singular Value Decomposition (SVD) compression may be used along the time dimension to accelerate both the matching and the spatial regularization that operates in the compressed domain as well as to enforce low-rank regularization.

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