Early gastric cancer image recognition method based on evolutionary neural network model compression

A neural network model, a technology for early gastric cancer, applied in biological neural network models, neural learning methods, character and pattern recognition, etc., can solve the problems of computational consumption and poor real-time performance, improve efficiency, reduce redundant parameters, promote The effect of actual clinical application

Active Publication Date: 2021-03-30
SICHUAN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to provide an image recognition method for early gastric cancer based on evolutionary neural network model compression based on the deficiencies of the prior art. The method is based on an evolutionary a

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  • Early gastric cancer image recognition method based on evolutionary neural network model compression
  • Early gastric cancer image recognition method based on evolutionary neural network model compression
  • Early gastric cancer image recognition method based on evolutionary neural network model compression

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Embodiment 1

[0048] Such as figure 1 As shown, the early gastric cancer identification method based on evolutionary neural network model compression provided in this embodiment includes the following steps:

[0049] (1) Collect and label early gastric cancer image datasets for training neural network models;

[0050] (2) Training the neural network model;

[0051] (3) Construct a binary encoding method to encode the parameters in the neural network model;

[0052] (4) Use evolutionary algorithms to compress the trained neural network model; reduce the amount of model calculation while maintaining network performance;

[0053] (5) Fine-tune the compressed neural network model and identify early gastric cancer lesion regions on newly input gastroscopy images.

[0054] Wherein, in the step (1), collecting and labeling the gastroscope image data set for training the neural network model includes the following steps:

[0055] (11) Record gastroscopy video streams, screen and cut out video c...

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Abstract

The invention discloses an early gastric cancer image recognition method based on evolutionary neural network model compression, relates to the technical field of computer application, and solves theproblems of parameter redundancy in an existing convolutional neural network model and poor real-time performance caused by large calculated amount consumption of the neural network model in an earlygastric cancer recognition process. The method comprises the following steps: collecting an early gastric cancer image data set; training a neural network model; constructing a binary encoding mode toencode parameters in the neural network model; compressing the trained neural network model by using an evolutionary algorithm; and finely adjusting the compressed neural network model, and identifying an early gastric cancer lesion area on a newly input gastroscopy image. According to the invention, the neural network model for detection can be compressed according to the collected gastroscopy image data, so that the efficiency of the neural network model in an early gastric cancer detection task is improved, and the deep neural network method has good real-time performance in the aspect ofearly gastric cancer detection.

Description

technical field [0001] The invention relates to the technical field of computer applications, in particular to an early gastric cancer image recognition method based on evolutionary neural network model compression. Background technique [0002] Gastric cancer (GC) is the third most lethal malignancy worldwide. Due to the mild early symptoms, gastric cancer is usually diagnosed at an advanced stage, and its 5-year survival rate is less than 30%. If gastric cancer is detected early and treated accordingly, its 5-year survival rate can increase to over 95%. Therefore, the identification of early gastric cancer is of great significance to reduce the mortality rate of gastric cancer. Gastroscopy has been widely used in the diagnosis of early gastric cancer, which can provide guidance for early intervention and treatment. Since early gastric cancer usually only shows some subtle changes in the mucosa, the sensitivity of gastric cancer identification is generally relatively low...

Claims

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Application Information

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IPC IPC(8): G06K9/32G06K9/62G06T7/00G06N3/04G06N3/08
CPCG06T7/0012G06N3/084G06N3/086G06T2207/10068G06T2207/20081G06T2207/20084G06T2207/20104G06T2207/30096G06T2207/30092G06V10/25G06V2201/032G06N3/045G06F18/23213G06F18/241G06F18/214
Inventor 胡兵章毅张潇之周尧刘伟吴雨袁湘蕾
Owner SICHUAN UNIV
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