Noise analysis systems and methods

Patent metadata

Field	Value
Publication number	US-12594048-B2
Application number	US-202318327018-A
Country	US
Kind code	B2
Filing date	May 31, 2023
Priority date	May 31, 2022
Publication date	Apr 7, 2026
Grant date	Apr 7, 2026

Abstract

A method and a system for noise analysis may be provided. A plurality of signals of a target object may be obtained. A first value of a first signal representation and a second value of a second signal representation of the target object may be determined based on the plurality of signals. A value of a noise parameter may be determined based on the first value of the first signal representation and the second value of the second signal representation.

First claim

What is claimed is:

1 . A method for noise analysis, implemented on at least one processor, comprising:
obtaining magnetic resonance (MR) data of a target object by using a magnetic resonance imaging (MRI) device to apply an MR pulse sequence to the target object; reconstructing a plurality of MR images of the target object based on the MR data; determining, based on the plurality of MR images, a first value of a first signal representation and a second value of a second signal representation of the target object, wherein the first signal representation and the second signal representation are defined as reciprocal with respect to each other; determining a noise parameter image based on the first value of the first signal representation and the second value of the second signal representation, wherein each pixel point in the noise parameter image corresponds to a physical point of the target object, and a pixel value of each pixel point is associated with a value of a noise parameter at its corresponding physical point; obtaining at least one noise reduction image by correcting at least one of the plurality of MR images based on the noise parameter image; and sending the at least one noise reduction image to a terminal for display.

2 . The method of claim 1 , wherein the plurality of MR images at least include a first group of images and a second group of images that are collected respectively in a first acquisition and a second acquisition performed by the MRI device.

3 . The method of claim 2 , wherein
the first group of images and the second group of images correspond to different values in a first target signal dimension.

4 . The method of claim 3 , wherein the first target signal dimension is a repetition dimension, and the first acquisition and the second acquisition are performed by applying a same pulse sequence in different scans.

5 . The method of claim 3 , wherein
the first group of images include a plurality of first images corresponding to different values in one or more reference second target signal dimensions, the second group of images include a plurality of second images corresponding to different values in the one or more reference second target signal dimensions, the one or more reference second target signal dimensions referring to one or more signal dimensions other than the first target signal dimension and a coil channel dimension.

6 . The method of claim 2 , wherein the first group of images include a plurality of first images corresponding to different values in at least one second target signal dimension, and the second group of images include a plurality of second images corresponding to different values in the at least one second target signal dimension.

7 . The method of claim 6 , wherein the MRI device includes a plurality of coil channels, and the at least one second target signal dimension at least includes a coil channel dimension.

8 . The method of claim 6 , wherein the plurality of first images and the plurality of second images are complex images.

9 . The method of claim 2 , wherein
the first signal representation is a ratio of the first group of images to the second group of images, and the second signal representation is a ratio of the second group of images to the first group of images.

10 . The method of claim 2 , wherein the MRI device includes a plurality of coil channels, the first group of images include a plurality of first MR images respectively collected by the coil channels in the first acquisition, and the second group of images include a plurality of second MR images respectively collected by the coil channels in the second acquisition.

11 . The method of claim 10 , wherein the first value of the first signal representation is an absolute value of the first signal representation, the second value of the second signal representation is an absolute value of the second signal representation, and the determining, based on the plurality of MR images, a first value of a first signal representation and a second value of a second signal representation of the target object includes:
for each of the plurality of coil channels, determining a first product of a conjugate image of the second image corresponding to the coil channel and the first image corresponding to the coil channel, a second product of a conjugate image of the first image corresponding to the coil channel and the second image corresponding to the coil channel, a third product of the conjugate image of the second image corresponding to the coil channel and the second image corresponding to the coil channel, and a fourth product of the conjugate image of the first image corresponding to the coil channel and the first image corresponding to the coil channel; designating a ratio of a sum of the first products of the plurality of coil channels to a sum of the third products of the plurality of coil channels as the first value of the first signal representation; and
designating a ratio of a sum of the second products of the plurality of coil channels to a sum of the fourth products of the plurality of coil channels as the second value of the second signal representation.

12 . The method of claim 1 , wherein the determining, based on the plurality of MR images, the first value of the first signal representation and the second value of the second signal representation includes:
determining the first value of the first signal representation and the second value of the second signal representation using a multi-dimensional integration (MDI) algorithm.

13 . The method of claim 1 , wherein the determining a noise parameter image based on the first value of the first signal representation and the second value of the second signal representation includes:
designating a product of the first value of the first signal representation and the second value of the second signal representation as the noise parameter image.

14 . The method of claim 1 , wherein the noise parameter image reflects a signal-to-noise ratio (SNR) of the plurality of MR images.

15 . The method of claim 1 , wherein the at least one of the plurality of images is corrected based on the noise parameter image by:
obtaining a correction mask according to the noise parameter image and a preset noise parameter threshold; and correcting the at least one of the plurality of images by applying the correction mask.

16 . The method of claim 1 , wherein
the obtaining MR data of a target object by using an MRI device to apply an MR pulse sequence to the target object comprises: obtaining first MR data of the target object by using the MRI device to apply the MR pulse sequence on the target object in a first acquisition; and obtaining second MR data of the target object by using the MRI device to apply the MR pulse sequence on the target object in a second acquisition; and the reconstructing a plurality of MR images of the target object based on the MR data comprises: reconstructing a first group of MR images based on the first MR data collected in the first acquisition, and reconstructing a second group of MR images based on the second MR data collected in the second acquisition.

17 . The method of claim 1 , wherein
the MR pulse sequence is a multi-echo sequence, the MR data includes first MR data collected in a first acquisition at a first echo time and second MR data collected in a second acquisition at a second echo time, the reconstructing a plurality of MR images of the target object based on the MR data comprises: reconstructing a first group of MR images based on the

Assignees

• Shanghai United Imaging Healthcare Co Ltd

Inventors

• Ye Yongquan

Classifications

• G06T7/0012

  Biomedical image inspection · CPC title

• G06T2207/30168

  Image quality inspection · CPC title

• G06T2207/10088

  Magnetic resonance imaging [MRI] · CPC title

• A61B6/501

  for diagnosis of the head, e.g. neuroimaging or craniography · CPC title

• A61B6/5258 Primary

  involving detection or reduction of artifacts or noise · CPC title