Pathological section color normalization method and system

A pathological slice and normalization technology, applied in the field of medical cytopathological image analysis, can solve the problem that the model is difficult to converge, and achieve the effect of improving the generation effect and ensuring the effect.

Active Publication Date: 2019-10-11
怀光智能科技(武汉)有限公司
View PDF5 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006]Aiming at the defects or urgent technical needs of the prior art, the present invention proposes a method and system for normalizing the color of pathological slices. Color-style pathological slice data is color-normalized to solve the problem that it is d...

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
  • Pathological section color normalization method and system
  • Pathological section color normalization method and system
  • Pathological section color normalization method and system

Examples

Experimental program
Comparison scheme
Effect test

example

[0083] Figure 4 The color style shown in (a) is the target color style. Figure 4 (b) is the color style that needs to be normalized. Figure 4 (c) The left one is the generation network G pair obtained by using the intra-domain discrimination loss and L1 loss as supervised training. Figure 4 The result of normalization of the image in (b) ; Figure 4 (c) The second from the left is the generation network G pair obtained by using intra-domain discrimination loss, inter-domain discrimination loss and L1 loss as supervised training. Figure 4 (b) The result after the image is normalized; Figure 4 (c) The left one is the generation network G pair obtained by using the intra-domain discrimination loss, inter-domain discrimination loss, L1 loss and task loss as supervised training. Figure 4 (b) The result after the image in (b) is normalized. It can be seen that the color styles generated under different loss supervisions have a high consistency with the target color style...

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 pathological section color normalization method and system, and the method comprises the steps: generating a picture of a target style through a generator, carrying out the discrimination of the generated picture and a real picture of the target style through a discrimination network, and executing the learning and discrimination adversarial training in a domain. In orderto reduce the difference between the generated picture of the non-target style picture and the target style picture, the generated picture of the non-target style picture and the target style pictureare identified through another identification network, inter-domain learning and identification confrontation training are executed, the difference between the generated picture of the non-target style picture and the target style picture is further reduced, and the performance of the generation network is optimized. According to the method, color normalization is carried out on pathological section data of different color styles, and the technical problems that a depth model trained under a single color style is difficult to have the same or similar performance in data of another color style, and the model is difficult to converge when pathological sections of different color styles are used as data to train the depth model are solved.

Description

technical field [0001] The invention belongs to the field of medical cytopathological image analysis, and more specifically relates to a method and system for normalizing the color of cytopathological slices from different sources. Background technique [0002] In recent years, artificial intelligence technology has developed rapidly, and the combination of artificial intelligence and medical care can alleviate the problem of shortage of doctor resources. In the field of medical cytopathology, the accumulation of a large amount of pathological slice data provides a big data background for the analysis of medical cytopathological images. In the processing of large data samples, because the analysis and processing capabilities of deep learning algorithms are generally stronger than other traditional analysis algorithms, depth Learning is widely used in the field of big data medical cytopathology image analysis. [0003] Using deep learning to analyze medical cytopathological ...

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): G06T3/00
CPCG06T3/0012
Inventor 刘秀丽余江盛余静雅陈西豪程胜华曾绍群
Owner 怀光智能科技(武汉)有限公司
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