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Image recognition module training method and device

An image recognition and training method technology, applied in the field of image processing, can solve the problem of low accuracy of medical image recognition

Pending Publication Date: 2021-05-18
THE FIRST MEDICAL CENT CHINESE PLA GENERAL HOSPITAL
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  • Description
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  • Application Information

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Problems solved by technology

[0014] The main purpose of this application is to provide an image recognition module training method and device to solve the problem of low accuracy of medical image recognition by the image recognition module trained through deep learning in the related art

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  • Image recognition module training method and device
  • Image recognition module training method and device

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Embodiment Construction

[0053] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the application. Obviously, the described embodiment is only It is an embodiment of a part of the application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0054] It should be noted that the terms "first" and "second" in the description and claims of the present application and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It should be understood that the data so used may be interchanged under appropriate circumstances for...

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Abstract

The invention discloses an image recognition module training method and device. The method comprises the steps of performing feature extraction on a specified medical image based on a convolutional neural network to generate a first image feature; processing the specified medical image based on an attention mechanism to obtain a second image feature and an extraction region; obtaining an extraction region image corresponding to the extraction region, namely, generating an extraction region image with a better training effect by secondary windowing in a progressive focusing mode; performing feature extraction on the extracted region image based on a convolutional neural network to obtain a third image feature of the extracted region image; and fusing the first image feature, the second image feature and the third image feature to obtain a fused image feature. According to the method, on the basis of global image learning, re-windowing can be carried out on the region of interest, input of the neural network is carried out in a progressive focusing mode, and the purpose of training the image recognition module through the multi-windowing image processing method based on the progressive focusing mechanism is achieved.

Description

technical field [0001] The present application relates to the technical field of image processing, in particular, to an image recognition module training method and device. Background technique [0002] From Roentgen's discovery of X-rays in 1895 to the present, the development of imaging has gone through a process from the original analog imaging to the current digital imaging. The application of imaging medicine in the modern medical and medical industry continues to expand, and it has become an indispensable part of modern medical diagnosis. [0003] In the current medical imaging diagnosis, doctors diagnose diseases by observing one or a group of two-dimensional images based on experience. With the development of computer technology, people gradually use computer image processing technology to analyze and process medical images, thus greatly improving the accuracy and reliability of diagnosis. [0004] Deep learning has become an important development direction in the ...

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Application Information

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IPC IPC(8): G06T7/00G06K9/62
CPCG06T7/0012G06T2207/10081G06T2207/20081G06T2207/20084G06V2201/03G06F18/253G06F18/214
Inventor 张涛
Owner THE FIRST MEDICAL CENT CHINESE PLA GENERAL HOSPITAL
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