Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Neural-network-based artifact correction method and apparatus of CT image

A neural network and CT image technology, applied in the medical field, can solve problems such as complicated reasons and inaccurate correction of artifacts, and achieve the effects of improving quality, accuracy and comprehensiveness

Active Publication Date: 2018-04-20
SHENZHEN ANKE HIGH TECH CO LTD
View PDF7 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, because the causes of artifacts in CT reconstruction results are quite complex, CT images can carry one or more artifacts, and each artifact is often caused by one or more reasons, which makes the CT image Artifacts cannot be corrected accurately

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
  • Neural-network-based artifact correction method and apparatus of CT image
  • Neural-network-based artifact correction method and apparatus of CT image
  • Neural-network-based artifact correction method and apparatus of CT image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The present invention provides a neural network-based CT image artifact correction method and device. In order to make the purpose, technical solution and effect of the present invention clearer and clearer, the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0045]Those skilled in the art will understand that unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the word "comprising" used in the description of the present invention refers to the presence of said features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, Integers, steps, operations, elements, components...

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 invention discloses a neural-network-based artifact correction method and apparatus of a CT image. The method comprises: preprocessing of CT data is carried out to generate a database carrying outan input sample of at least one kind of artifact; a neural network for correcting the at least one kind of artifact is constructed; the input sample is inputted into the neural network and the neuralnetwork is trained by a preset objective function to obtain a trained neural network; and a to-be-processed CT image is inputted into the trained neural network to carry out artifact identification and correction, and a corrected CT image and an identified artifact image are outputted. On the basis of deep learning, the CT image including multiple kinds of artifacts is processed by the neural network, so that the quality of the CT image is improved.

Description

technical field [0001] The invention relates to the field of medical technology, in particular to a neural network-based artifact correction method and device for CT images. Background technique [0002] CT (computed tomography imaging system) uses X-rays to scan objects to obtain projection data, and process these projection data through tomographic reconstruction algorithms to obtain the object's section and three-dimensional density information to achieve the purpose of non-destructive testing. It has important applications in medical diagnosis, industrial non-destructive testing and other fields. In the field of medical diagnosis, CT has become the three key medical imaging systems together with magnetic resonance (MRI), positron emission tomography and CT combination system (PET / CT) since its advent in 1970. Compared with other imaging methods, CT reconstruction can quickly obtain high-resolution images, the contrast accuracy of the reconstruction results can be contro...

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
IPC IPC(8): G06T5/00G06N3/08
CPCG06T2207/20084G06T2207/20081G06T2207/10081G06T5/73
Inventor 曾凯吴小页徐丹
Owner SHENZHEN ANKE HIGH TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com