Image data generation method and device

An image data and image generation technology, applied in the field of image processing, can solve the problem that the data generation method cannot provide effective training samples for the artificial intelligence medical image analysis process.

Pending Publication Date: 2020-08-07
PING AN TECH (SHENZHEN) CO LTD
View PDF2 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, the present invention provides a method and device for generating image data, the main purpose of which is to solve the problem that the data generation method in the prior art cannot provide effective training samples for the artificial intelligence medical image analysis process

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 data generation method and device
  • Image data generation method and device
  • Image data generation method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0025] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0026] Insufficient training samples of lesion data and labeled lesion data are the biggest obstacle to the improvement of the performance of artificial intelligence medical image analysis. Taking cerebral hemorrhage detection as an example, cerebral hemorrhage is not a frequently-occurring disease, and most of the head CT images are negative. ), there are about 1,000 cases of cerebral hemorrhage in an ordinary hospital a year, and ...

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 an image data generation method and device, relates to the technical field of image processing, and aims to solve the problem that a data generation method in the prior art cannot provide effective training data samples for an artificial intelligence medical image analysis process. The method mainly comprises the following steps: acquiring a focus-free image; generating a predicted lesion mask according to a preset lesion contour; and inputting the focus-free image and the predicted focus mask into an image generation model to generate a predicted focus image, the imagegeneration model being generated by training a marked focus training picture. The method is mainly applied to the process of expanding the image data.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method and device for generating image data. Background technique [0002] With the continuous improvement and improvement of deep learning algorithms, artificial intelligence medical image analysis can be used to detect and identify lesions. Artificial intelligence medical image analysis is usually based on data-driven supervised learning, which uses a posterior model based on various features, and the posterior model requires a large amount of manually labeled data for training. However, positive image data with diseases and manual annotation are not easy to obtain, which makes it difficult to improve the performance of artificial intelligence medical image analysis. Taking cerebral hemorrhage data as an example, cerebral hemorrhage is not a frequent disease, and most CT images of the head are negative. Even if a certain amount of positive data can be collected, it ...

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): G06T7/00G06T7/12G16H30/40
CPCG06T7/0014G06T7/12G16H30/40G06T2207/10072G06T2207/10132G06T2207/20081G06T2207/20221G06T2207/30016G06T2207/20101
Inventor 卓柏全周鑫陈凯星章古月
Owner PING AN TECH (SHENZHEN) CO LTD
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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap