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

NBI image processing method based on deep learning and image enhancement and application thereof

A technology of image enhancement and deep learning, applied in image enhancement, image data processing, medical images, etc., to achieve the effect of accurate diagnosis

Active Publication Date: 2019-08-30
WUHAN ENDOANGEL MEDICAL TECH CO LTD
View PDF7 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to use deep learning algorithm and image enhancement technology to extract features such as microvessels and microstructures of NBI pictures, present the characterized pictures to endoscopists, overcome the bottleneck of the existing technology, and use artificial intelligence to make Doctors give more accurate auxiliary diagnosis opinions on early cancer under NBI

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
  • NBI image processing method based on deep learning and image enhancement and application thereof
  • NBI image processing method based on deep learning and image enhancement and application thereof
  • NBI image processing method based on deep learning and image enhancement and application thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] The technical scheme of the present invention will be further described below in conjunction with the drawings and embodiments.

[0039] Such as figure 1 As shown, the NBI image processing method based on deep learning and image enhancement provided by the present invention includes the following steps

[0040] Step S1, collecting a large number of NBI early gastric cancer or non-cancerous enlarged images;

[0041] Step S2: The white areas and blood vessels in the image are marked by a professional physician, so that the original NBI image with complex background and structure is transformed into a simple stroke image (annotated image) with clear features, such as figure 2 Shown

[0042] Step S3, the original NBI image and the annotated image are input into the deep convolutional neural network model for training. The deep convolutional neural network model continuously calculates the prominent information features between the original image and the annotated image (such as: t...

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 NBI image processing method based on deep learning and image enhancement and an application of the NBI image processing method. The method is characterized by extracting thefeatures, such as the microvessels, the microstructures, etc., of the NBI images by using a deep learning algorithm and an image enhancement technology, displaying the featured images to an endoscopic doctor, so that the bottleneck in the prior art is overcome, and the doctor gives the more accurate auxiliary diagnosis suggestions for the early cancer under NBI by using the artificial intelligence. According to the images processed by the method disclosed by the invention, the focus area in the stomach early cancer image is enhanced, the boundary of the focus and the normal area becomes clearer through the highlight processing, the doctor can be assisted to judge whether the patient suffers from the early cancer or not with reference to the processed image during diagnosis, and the situation that the focus is missed due to the too fast gastroscopy or the fatigue operation of the doctor is avoided.

Description

Technical field [0001] The invention belongs to the field of medical detection assistance, and specifically relates to an artificial intelligence-based early gastric cancer auxiliary diagnosis method. Background technique [0002] Gastric cancer is one of the common malignant tumors in my country, and its incidence ranks first among digestive system tumors. In 2015, there were 679,000 new cases of gastric cancer and 498,000 deaths in my country, accounting for about 1 / 5 of the total cancer deaths. The fundamental reason that malignant tumors endanger human health is that it is difficult to detect early. If gastrointestinal tumors are diagnosed in the early stage, the 5-year survival rate of patients can be higher than 90%, and if it progresses to the middle and advanced stages, the 5-year survival rate of patients is only 5-25%. Therefore, early diagnosis is an important strategy to improve patient survival. [0003] Endoscopy is the most commonly used powerful tool to detect ea...

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): G06T7/00G06T7/41G06T7/90G16H30/40
CPCG06T7/0012G06T2207/20081G06T2207/20084G06T2207/30092G06T7/41G06T7/90G16H30/40
Inventor 胡珊
Owner WUHAN ENDOANGEL MEDICAL 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