Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Image reconstruction method, device, equipment and storage medium

An image reconstruction and image reconstruction technology, applied in the field of image processing, can solve the problem of long image reconstruction time, and achieve the effect of ensuring the image reconstruction accuracy, shortening the image reconstruction time, and improving the reconstruction speed.

Active Publication Date: 2022-01-28
SHENZHEN INST OF ADVANCED TECH
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of this, the embodiment of the present application provides an image reconstruction method, device, device, and storage medium to solve the problem of long image reconstruction time in the prior art when performing image reconstruction based on the number of undersampling in a non-Cartesian coordinate system. technical issues

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Image reconstruction method, device, equipment and storage medium
  • Image reconstruction method, device, equipment and storage medium
  • Image reconstruction method, device, equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0051]In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

[0052] It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude one or more other Presence or addition of features, wholes, steps, operations, elements, components and / or collections thereof.

[0053] In additio...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The present application belongs to the technical field of image processing, and provides an image reconstruction method, apparatus, device and storage medium. The method obtains the sampling data of the target object; the sampling data is input into the deep learning network after training for processing, and the reconstructed image corresponding to the sampling data is obtained, wherein the sampling data is obtained based on a preset sampling mode in a non-Cartesian coordinate system. Under-sampling frequency-domain data; compared to the prior art technical solution for image reconstruction based on non-uniform fast Fourier transform on under-sampling frequency-domain data in a non-Cartesian coordinate system, the deep learning network in the embodiment of the present application undergoes image reconstruction. Pre-training can directly reconstruct the corresponding image according to the input undersampling frequency domain data in the non-Cartesian coordinate system, without manual selection / adjustment of parameters such as scale factors, which improves the undersampling frequency in the non-Cartesian coordinate system. Reconstruction speed of domain data.

Description

technical field [0001] The present application relates to the technical field of image processing, and in particular to an image reconstruction method, device, equipment and storage medium. Background technique [0002] In current medical imaging, such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), sampling of the target object is required. Image reconstruction is performed on the data to form a high-definition image of the scanned area. [0003] Taking magnetic resonance imaging (MRI) as an example, in order to enhance the clinical practicability of magnetic resonance imaging technology and shorten the scanning time, magnetic resonance equipment often adopts data sampling far below the Nyquist sampling frequency to obtain target objects in non-Cartesian The undersampled frequency domain data in the non-Cartesian coordinate system is then image reconstructed to form a high-definition image of the target object. [000...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06T11/00
CPCG06T11/003
Inventor 王珊珊郑海荣祁可翰刘新
Owner SHENZHEN INST OF ADVANCED TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products