Unlock instant, AI-driven research and patent intelligence for your innovation.

Medical image super-resolution reconstruction method based on deep learning

A super-resolution reconstruction and medical imaging technology, applied in medical imaging, informatics, image data processing, etc., can solve problems such as the imbalance of yin and yang samples, and achieve the effect of ensuring validity and stability

Active Publication Date: 2019-07-16
BEIJING UNIV OF TECH
View PDF4 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] (1) Aiming at the characteristics of medical images, using the additional annotation information of medical datasets, a new dataset production and training strategy is proposed to solve the problem of imbalance between yin and yang samples. This method will be referred to as PN-samplebalance in the following.

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
  • Medical image super-resolution reconstruction method based on deep learning
  • Medical image super-resolution reconstruction method based on deep learning
  • Medical image super-resolution reconstruction method based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] In order to make the object, technical solution and advantages of the present invention clearer, the following in conjunction with the attached Figure 1-5 And embodiment, the present invention is described in further detail. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not constitute conflicts with each other.

[0018] The present invention provides a method and system for medical image super-resolution reconstruction based on deep learning. Inputting medical images directly into the system yields correct super-resolution results. A large amount of high-quality medical image data is used to train the network. The difference from other methods is that we introduce the location information of the lesio...

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 provides a medical image super-resolution reconstruction method based on deep learning. A correct super-resolution result can be obtained by directly inputting the medical image into thesystem; the network is trained through a large amount of high-quality medical image data; position information of a focus in medical image data is introduced in a training stage; wherein the positioninformation refers to central coordinates and sizes of focuses or fine edge annotations of the focuses, and by adding the prior information, the problem that medical images with super-resolution loseoriginal imaging significance due to the fact that medical image super-resolution network training is inclined in other methods can be solved.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a medical image super-resolution reconstruction method based on deep learning. Background technique [0002] With the development of deep learning, the level of computer vision and image processing is constantly breaking through the bottleneck of traditional methods in some scenarios. As an important technology in computer vision, image super-resolution is also flourishing. Super-resolution methods based on deep learning in natural scenes emerge in endlessly, and a variety of different network design patterns have also been derived. The network depth continues to increase, feature reuse capabilities continue to increase, and PSNR indicators at different scales are also rising. In video It has a wide range of applications in practical scenarios such as surveillance, video restoration, digital high-definition, and satellite images. [0003] Due to the limitati...

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 Applications(China)
IPC IPC(8): G06T3/40G16H30/00
CPCG06T3/4053G06T3/4046G16H30/00Y02T10/40
Inventor 刘蓬博王瑾朱青
Owner BEIJING UNIV OF TECH