Research On Deep Learning Algorithm And Its Application In Medical Imaging Diagnosis

The level of medical diagnosis affects the lives of people.At present,the amount of medical data is increasing day by day,but it is very important to make good use of this huge medical data to contribute to the medical cause.Clinical medical imaging is a very representative kind of medical big data.With the development of medical imaging technology,a large amount of medical imaging data is produced in clinical practice.At the same time,there is a lot of invalid information and interference in these imaging data factor.In order to accurately diagnose the disease,it is necessary to accurately find the effective information in the medical image.At the same time,deep learning technology is excellent in solving many problems such as visual recognition,speech recognition and natural language processing.Therefore,this article is mainly based on deep learning techniques to mine the available information in medical images.This article first analyzes and studies some classic machine learning related algorithms,and focuses on the BP neural network model,the traditional convolutional neural network model and the VGG model.Then,the traditional medical image diagnosis methods are studied and summarized,and the four aspects of image denoising,image segmentation,feature extraction,and image classification are introduced,and their defects and deficiencies are analyzed.Finally,for the two clinical medical images of ovarian cancer and new coronavirus pneumonia,based on deep learning technology,an intelligent discrimination model of ovarian cancer and new coronavirus pneumonia was established.By performing image processing on related images,including image denoising,grayscale processing,Gaussian filtering,image scaling,and then adjusting different parameters for experiments,the best diagnostic model is established to achieve ovarian cancer and new coronary pneumonia Auxiliary diagnosis.The experimental results show that deep learning technology can be applied to medical imaging diagnosis.For ovarian cancer,the recall rate of classification results reaches 0.90.For new coronavirus pneumonia,the diagnostic recall rate reaches 0.96.