Medical image classification method, model training method and server

A medical image and classification method technology, applied in medical image, image analysis, neural learning methods, etc., can solve problems such as low efficiency, mixed quality, and high cost

Active Publication Date: 2019-11-08
TENCENT TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In this way, not only is it inefficient, but it is also very easy to mix in low-quality or invalid data
The existing microscope image annotation technology has low annotation reliability, high cost and long cycle to obtain valid data

Method used

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  • Medical image classification method, model training method and server
  • Medical image classification method, model training method and server
  • Medical image classification method, model training method and server

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Embodiment Construction

[0061] The following description provides specific details for a thorough understanding and practice of various embodiments of the present disclosure. It should be understood by those skilled in the art that the technical solutions of the present disclosure may be practiced without some of these details. In some instances, well-known structures and functions have not been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments of the present disclosure. Terms used in this disclosure are to be interpreted in their broadest reasonable manner, even though they are used in connection with specific embodiments of this disclosure.

[0062] First of all, some terms involved in the embodiments of the present disclosure will be described to facilitate the understanding of those skilled in the art.

[0063] Out of focus: When the microscope objective lens focuses on the pathological section, or the camera fails to reach or exceed the reasonable ...

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Abstract

The invention mainly relates to the technical field of deep learning of artificial intelligence. The invention discloses a medical image classification method, a model training method and a server. The medical image classification method comprises the steps of obtaining a data set of medical images; performing quality analysis on the data set of the medical image, and extracting feature information of the medical image, the quality analysis including one or more of color gamut-saturation-brightness analysis, sharpness analysis, texture analysis and entropy analysis; and based on the extractedfeature information, classifying the medical image by using a pre-trained deep learning network used for performing anomaly detection classification on the medical image to obtain a classification result, the classification including one or more of classification for determining whether the medical image is a normal tissue, an unrelated tissue, lens defocusing and white balance failure.

Description

technical field [0001] The invention relates to the technical field of deep learning of artificial intelligence, in particular to a classification method of microscope images, a model training method and a server. Background technique [0002] The solutions provided in the embodiments of the present application involve technologies such as deep learning of artificial intelligence. Artificial Intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the nature of intelligence and produce a new kind of intelligent machine that can respond in a similar way to human intelligence. Artificial intelligence is to study the design principles an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/90G06T7/155G06T7/13G06T7/00G06T5/00G06T3/40G06N3/08G06N3/04
CPCG06T5/002G06T7/155G06T7/13G06T3/4007G06T7/90G06T7/0012G06N3/08G06T2207/30168G06N3/045G06T1/20G06T2207/10056G06T2207/20081G06T2207/20084G06T2207/30024G06T2207/30096G06T2207/20076G16H50/70G16H50/20G16H30/40G16H30/20G06T2207/30004
Inventor 肖凯文韩骁叶虎周昵昀
Owner TENCENT TECH (SHENZHEN) CO LTD
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