Adaptive reconstruction of MR data

Patent metadata

Field	Value
Publication number	US-11719779-B2
Application number	US-202217662280-A
Country	US
Kind code	B2
Filing date	May 6, 2022
Priority date	May 6, 2021
Publication date	Aug 8, 2023
Grant date	Aug 8, 2023

Abstract

An adaptive reconstruction of MR data, including acquired MR data of a core region having core segments and simulated MR data of a peripheral region. The method includes ascertaining a peripheral signal based on the MR data of the peripheral region, determining a scaling factor for each core segment by taking into account the peripheral signal and a mean signal intensity of the MR data for the respective core segment, scaling the MR data of the core region by taking into account the MR data of each core segment and that of the scaling factor corresponding to the respective core segment, generating filtered MR data by combining the scaled MR data of the core region with the MR data of the peripheral region, and reconstructing image data from the filtered MR data.

First claim

The invention claimed is:

1. A method for an adaptive reconstruction of magnetic resonance (MR) data, comprising:
providing MR data including MR data of a core region of a k-space and MR data of a peripheral region of the k-space, wherein:
the core region of the k-space comprises at least three core segments,
each core segment of the at least three core segments includes mutually parallel k-space rows and the core segments are arranged relative to each other in such a way that the parallel k-space rows incorporated by therein are mutually parallel,
the MR data of the peripheral region comprises a simulated signal not equal to zero, and
the MR data of the core region is acquired by multiple time-sequential carrying out of steps in order in each case to capture the MR data of an echo train, wherein the steps comprise:
switching an excitation pulse; and
switching a plurality of refocusing pulses,
wherein between two successive refocusing pulses, one reading out each takes place of a k-space row, with each echo of the echo train, associated with one of the at least three core segments,

ascertaining a peripheral signal based on the MR data of the peripheral region;
determining a scaling factor for each of the core segments by taking into account the peripheral signal and a mean signal intensity of the MR data for the respective core segment;
scaling the MR data of the core region by taking into account the MR data of each of the core segments and that of the scaling factor corresponding to the respective core segment;
generating filtered MR data by combining the scaled MR data of the core region with the MR data of the peripheral region; and
reconstructing image data from the filtered MR data.

2. The method as claimed in claim 1 , wherein the scaling factor is determined such that a difference between the peripheral signal and the mean signal intensity of the MR data of a core segment adjacent to the peripheral region is minimized.

3. The method as claimed in claim 1 , wherein the scaling factor is determined by taking into account a time interval dt of reading out a k-space row associated with the respective core segment relating to the excitation pulse.

4. The method as claimed in claim 3 , wherein the time interval dt influences the scaling factor S in accordance with a dependence S˜exp(−T 2 /dt), where T 2 is a mean T 2 relaxation time of at least one section of an examination region.

5. The method as claimed in claim 3 , wherein the time interval dt influences the scaling factor S in accordance with dependence S=A*exp(−T 2 /dt)+B, where T 2 is a mean T 2 relaxation time of at least one section of an examination region, and A and B are optimization parameters in a context of determination of the scaling factor.

6. The method as claimed in claim 5 , wherein A and B are optimized such that a difference between the peripheral signal and the mean signal intensity of MR data of two core segments, directly adjoining the peripheral region, of the at least three core segments is minimized.

7. The method as claimed in claim 5 , wherein A and B are optimized such that the scaling factor equal to one is assigned to the core segment comprising MR data with the time interval dt corresponding to a defined echo time.

8. The method as claimed in claim 1 , wherein the MR data of the peripheral region comprises a signal simulated by using a neural network.

9. The method as claimed in claim 3 , wherein the time interval dt of reading out all k-space rows associated with one core segment of the at least three core segments is the same as the excitation pulse of the corresponding echo train.

10. The method as claimed in claim 3 , wherein the time interval dt of reading out k-space rows associated with at least one core segment of the at least three core segments is different from the excitation pulse of the corresponding echo train.

11. A reconstruction unit, comprising:
an ascertainment unit; and
a scaling unit, which is configured to carry out a method for an adaptive reconstruction of MR data as claimed in claim 1 .

12. A magnetic resonance device with a control unit comprising a reconstruction unit, which is configured to carry out a method for an adaptive reconstruction of MR data as claimed in claim 1 .

13. A non-transitory computer program product, which comprises a program and is loadable directly into a memory of a programmable reconstruction unit to carry out a method for an adaptive reconstruction of MR data as claimed in claim 1 when the program is executed in the programmable reconstruction unit.

Assignees

• Siemens Healthcare Gmbh

Inventors

• Paul Dominik
• Nickel Marcel Dominik
• Dispenza Nadine
• Bauer Simon

Classifications

• G01R33/5608 Primary

  Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels (image data processing or generation, in general G06T) · CPC title

• G01R33/4818

  MR characterised by data acquisition along a specific k-space trajectory or by the temporal order of k-space coverage, e.g. centric or segmented coverage of k-space · CPC title

• G01R33/5676

  Gating or triggering based on an MR signal, e.g. involving one or more navigator echoes for motion monitoring and correction · CPC title

• G01R33/54 Primary

  Signal processing systems, e.g. using pulse sequences {; Generation or control of pulse sequences; Operator console} · CPC title

• G01R33/5617 Primary

  using RF refocusing, e.g. RARE · CPC title