Algorithm improvement of biomimetic pattern recognition in imaging pneumonia discrimination

Abstract

The invention discloses an algorithm improvement of biomimetic pattern recognition in imaging pneumonia discrimination. A healthy X-ray film, a viral pneumonia X-ray film and a bacterial pneumonia X-ray film are normalized into experimental images with the same size; the experimental image I after the normalization of the healthy X-ray film image is input into a convolutional neural network to extract an image feature vector; wherein the convolutional neural network comprises a convolutional layer, a pooling layer and a full connection layer. The image feature vector extraction method comprises the steps of A, carrying out convolution on an experimental image I and a convolution kernel, and outputting a result through an activation function to form a feature map 01 of the convolutional layer; carrying out convolution on the feature map 01 and a next convolution kernel, and outputting a result through an activation function to form a feature map 02 of a convolution layer; and the feature map 02 enters a pooling layer as an input image.

Description

technical field [0001] The invention belongs to the field of image recognition, and relates to the algorithm improvement of bionic pattern recognition in imaging pneumonia discrimination. Background technique [0002] Artificial intelligence has achieved many innovations in many industries, improving not only work efficiency, but also accuracy. As far as the medical field is concerned, artificial intelligence has been applied to clinical diagnosis problems, but the application of artificial intelligence to the field of medical imaging started relatively late. The reason is that the artificial intelligence used for medical imaging diagnosis must rely on human subjectivity to establish mathematical models. Support Vector Machine Classifiers Reduce Intra-Scan Variation in HRCT Classification of Regional Disease Patterns in Diffuse Lung Disease: Comparison with Bayesian Classifiers, A Support Vector Machine with Bayesian Based Algorithm Using 22 Quantitative Features To judge p...

AI Technical Summary

Problems solved by technology

[0003] The discrimination of pneumonia type is of great significance to its treatment. Traditionally, computer-aided discrimination is used, and the method of support vector machine is usually used, but when the data increases, the accuracy drops seriously.

Images