Vascular guided wave elastography method and system based on machine learning

A technology of elastography and machine learning, which is applied in the field of medical imaging, can solve the problems of large errors and limitations, and achieve the effects of small measurement errors, easy operation, and improved measurement accuracy

Active Publication Date: 2020-04-24
TSINGHUA UNIV
View PDF5 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since the wavelength of B-ultrasound is comparable to the thickness of blood vessels in magnitude, the actual measurement of blood vessel thickness with B-ultrasound often has large errors, which limits the further application of this method.

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
  • Vascular guided wave elastography method and system based on machine learning
  • Vascular guided wave elastography method and system based on machine learning
  • Vascular guided wave elastography method and system based on machine learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0035]Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0036] The vascular guided wave elastography method and system based on machine learning according to the embodiments of the present invention will be described below with reference to the accompanying drawings. First, the vascular guided wave elastography method based on machine learning according to the embodiments of the present invention will be described with reference to the accompanying drawings.

[0037] Shear wave elastography has attracted extensive attention in the medical field. By analyzing the propagation of shear wav...

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 blood vessel guided wave elastic imaging method and system based on machine learning. The blood vessel guided wave elastic imaging method comprises the steps that numerical simulation is conducted on propagation of shear waves in a thin layer system of a blood vessel through finite element software, and a finite element analysis result is obtained; motion speed distribution of nodes in the whole field is obtained according to the finite element analysis result, the motion speeds of the nodes on the center line of a thin layer are extracted, and a frequency dispersioncurve is obtained to serve as an input signal of a neural network; and a training set and a test set of the neutral network are obtained according to the frequency dispersion curve, training is conducted through a neutral network method till the error on the training set is less than a preset value, and a blood vessel guided wave elastic imaged picture is obtained through the final neutral network. According to the blood vessel guided wave elastic imaging method, the measuring precision of blood vessel mechanical properties can be improved, good extensibility is achieved, in-vivo noninvasive rapid measurement of the blood vessel elastic property is achieved, operation is easy and convenient, and the measurement error is small.

Description

technical field [0001] The invention relates to the technical field of medical imaging, in particular to a machine learning-based vascular guided wave elastography method and system. Background technique [0002] Cardiovascular system diseases are the number one killer of human health in many countries and regions. Cardiovascular system diseases, such as arteriosclerosis and vascular plaque, will be accompanied by significant changes in the mechanical properties of blood vessels. In addition, some studies have confirmed that diabetes can lead to changes in the mechanical properties of blood vessels. Therefore, measuring the mechanical properties of blood vessels in vivo is of great significance for the early screening and diagnosis of many diseases. In related technologies, the mechanical properties of blood vessels are generally evaluated clinically by measuring the pulse wave velocity (Pulse Wave Velocity, PWV for short). However, this method can only roughly calculate t...

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): A61B8/08
CPCA61B8/0891A61B8/485A61B8/5207A61B8/5215
Inventor 曹艳平郑阳李国洋
Owner TSINGHUA UNIV
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
Try Eureka
PatSnap group products