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Artificial intelligence diagnosis method for gastric cancer under narrow-band imaging amplification gastroscope

A technology of artificial intelligence and diagnostic methods, applied in the field of medical technology assistance, can solve problems such as unclear microstructure diagrams of microvessels

Pending Publication Date: 2021-03-02
WUHAN ENDOANGEL MEDICAL TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the microvessels and microstructure diagrams displayed by the invention patent are not very clear, and doctors need to observe the microvessels and microstructure diagrams

Method used

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  • Artificial intelligence diagnosis method for gastric cancer under narrow-band imaging amplification gastroscope
  • Artificial intelligence diagnosis method for gastric cancer under narrow-band imaging amplification gastroscope
  • Artificial intelligence diagnosis method for gastric cancer under narrow-band imaging amplification gastroscope

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Embodiment Construction

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0054] The invention provides a technical solution: an artificial intelligence diagnosis method for gastric cancer under a narrow-band imaging magnifying gastroscope, comprising the following steps: comprising the following steps:

[0055] S1. Construct a mini-UNet neural network model. According to the characteristics of the significant difference between the effective image area and the black area and text area of ​​the static image of the narrow-band imagin...

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Abstract

The invention relates to the technical field of medical technology assistance, in particular to an artificial intelligence diagnosis method for gastric cancer under a narrow-band imaging amplificationgastroscope, which comprises the following steps: S1, constructing a mini-UNet neural network model; S2, constructing a UNet + + image segmentation neural network model, and obtaining an area ratio Rabnormal of an image feature difference region; S3, adopting a generative adversarial network (GAN) technology to obtain a microvascular morphological diagram and a microstructure morphological diagram of the feature abnormal region; S4, identifying the microvessel form dissimilarity degree and the microstructure form dissimilarity degree in the microvessel form diagram and the microstructure formdiagram by the neural network model ResNet50; and S5, carrying out identification and judgment by using the random forest model obtained by training to obtain final judgment of cancer or non-cancer,and identifying the canceration position range of the image, which is judged to be cancer, as the identified image feature difference region Pabnormal. The sensitivity and specificity of the kit to cancer and non-cancer recognition reach about 93.4% and 90.7% respectively, a clinician can be effectively assisted in discriminating and diagnosing cancer and non-cancer, and a canceration position range is given.

Description

technical field [0001] The invention relates to the field of medical technology auxiliary technology, in particular to an artificial intelligence diagnosis method for gastric cancer under a narrow-band imaging magnifying gastroscope. Background technique [0002] Gastric cancer is a malignant tumor of the gastric mucosal epithelium. Endoscopy is the most important means of gastric cancer screening, especially the Magnifying Endoscopy with Narrow Band Imaging (ME-NBI) technology can capture high-definition enlarged gastric mucosal images , Doctors are of great help to accurate diagnosis by observing the extent of the lesion area in the image, the microvessels and microstructure of the lesion area. [0003] In recent years, with the rapid development of computer artificial intelligence technology, the application of artificial intelligence, deep learning, convolutional neural network and other technologies in the medical field has gradually increased, and they are used for aux...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/62
CPCG06T7/0012G06T7/62G06T2207/10068G06T2207/20081G06T2207/20084G06T2207/30092G06T2207/30096
Inventor 郑碧清刘奇为于天成胡珊
Owner WUHAN ENDOANGEL MEDICAL TECH CO LTD
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