Convolution neural network migration method, device, electronic device and storage medium

A convolutional neural network and screening technology, applied in the field of medical image processing, can solve the problems that the convolutional neural network cannot directly apply high-resolution input images, occupy large computing resources, etc.

Active Publication Date: 2018-12-28
北京致远慧图科技有限公司
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Problems solved by technology

[0006] In view of the above-mentioned technical problems in the prior art, embodiments of the present disclosure propose a convolutional neural network migration method, device, electronic equipment, and computer-readable storage medium to solve the problem that the existing convolutional neural network cannot be directly applied to high-resolution High-rate input images, and solve the problem of developing a dedicated convolutional neural network that takes up large computing resources

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  • Convolution neural network migration method, device, electronic device and storage medium
  • Convolution neural network migration method, device, electronic device and storage medium
  • Convolution neural network migration method, device, electronic device and storage medium

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[0047] In the following detailed description, numerous specific details of the disclosure are set forth by way of example in order to provide a thorough understanding of the relevant disclosure. It will be apparent, however, to one of ordinary skill in the art that the present disclosure may be practiced without these details. It should be understood that the terms "system", "device", "unit" and / or "module" used in the present disclosure are used as a means of distinguishing between different parts, elements, sections or assemblies at different levels in a sequential arrangement. method. However, these terms may be replaced by other expressions if the same purpose can be achieved by other expressions.

[0048]It will be understood that when a device, unit or module is referred to as being "on," "connected to" or "coupled to" another device, unit or module, it can be directly on the other device, unit or module. connected or coupled to or communicate with other devices, units...

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Abstract

Embodiments of the present disclosure disclose a convolution neural network migration method. The method comprises the steps of: improving the last pooling layer of the first convolution neural network to obtain a second convolution neural network so that the resolution of the input image of the second convolution neural network is greater than the resolution of the input image of the first convolution neural network. The method is suitable for input data sets of different sizes, such as high resolution fundus images, and saves the computational resources consumed in the development of specialconvolutional neural networks.

Description

technical field [0001] The present disclosure relates to the field of medical image processing, in particular to a convolutional neural network migration method, device, electronic equipment and storage medium. Background technique [0002] With the breakthrough of artificial intelligence technology, the application of new artificial intelligence in the field of medical image processing, especially the machine learning method based on massive data, is becoming an emerging research and application hotspot. Among them, the automatic identification of diabetic retinopathy is a rapidly emerging branch. [0003] When using fundus images of patients for Diabetic retinopathy (Diabetic retinopathy, DR) screening, no matter through manual or automated methods, it is necessary to determine whether the patient has received laser photocoagulation before, because whether laser photocoagulation has been received Surgical treatment will affect the classification of DR in subsequent screen...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06T7/00G06N3/08G06N3/04
CPCG06N3/08G06T7/0012G06T2207/20084G06T2207/20081G06T2207/30041G06T2207/30096G06N3/045G06F18/241
Inventor 魏奇杰王皓丁大勇
Owner 北京致远慧图科技有限公司
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