The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 14, 2023

Filed:

Jul. 05, 2023
Applicant:

Institute of Automation, Chinese Academy of Sciences, Beijing, CN;

Inventors:

Jie Tian, Beijing, CN;

Zechen Wei, Beijing, CN;

Hui Hui, Beijing, CN;

Xin Yang, Beijing, CN;

Huiling Peng, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06T 11/00 (2006.01); G06T 5/00 (2006.01); G06T 5/10 (2006.01); A61B 5/0515 (2021.01);
U.S. Cl.
CPC ...
G06T 11/006 (2013.01); A61B 5/0515 (2013.01); G06T 5/002 (2013.01); G06T 5/10 (2013.01); G06T 2207/10072 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

A method and system for reconstructing a magnetic particle distribution model based on time-frequency spectrum enhancement are provided. The method includes: scanning, by a magnetic particle imaging (MPI) device, a scan target to acquire a one-dimensional time-domain signal of the scan target; performing short-time Fourier transform to acquire a time-frequency spectrum; acquiring, by a deep neural network (DNN) fused with a self-attention mechanism, a denoised time-frequency spectrum; acquiring a high-quality magnetic particle time-domain signal; and reconstructing a magnetic particle distribution model. The method learns global and local information in the time-frequency spectrum through the DNN fused with the self-attention mechanism, thereby learning a relationship between different harmonics to distinguish between a particle signal and a noise signal. The method combines the global and local information to complete denoising of the time-frequency spectrum, thereby acquiring the high-quality magnetic particle time-domain signal.


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