Application And Research Of Computer To Silicosis Early Diagnosis And Prediction

The silicosis is the most important occupational disease of our country, not only the number of patients is numerous but also great harm. The basic plan of research and analysis is based on intuition for some of the data the researchers and conducted a survey in order to achieve some verification of the researchers assume. In this context, we have in-depth study of the technology of computer- assisted treatment of silicosis.Firstly, in order to make better use of computer-assisted methods to assist diagnosis of silicosis, in order to understand the patient's medical history, computer-aided diagnosis has been an entry point to find the integration points between the diagnosis of silicosis and computer-aided technology.Secondly, we have summarized and systemized the classification process of silicosis in X-ray image, investigated in several key processes of image classification, including: view Fig selection, data cleaning, as well as the extraction method of characteristic parameters, and then proposed a , based on ID3 decision tree algorithm , automatic classification method of the silicosis patients X-ray images. Thereby reducing the difficulty of early diagnosis of silicosis is conducive to reducing the rate of missed diagnosis of pneumoconiosis.Then, we also proposed the silicosis disease predict method based on non-extraction Haar wavelet transform: First, with the recurrence-free extract Haar wavelet dock workers exposed to dust and dust exposure, dust of time, smoking and many other factors in the time series decomposition. Then in the wavelet decomposition detail signal and approximation signal logistic has adopted model and sliding window-type polynomial fitting. The algorithm can solve the model prediction of silicosis in the parameter adjustment problems, with good accuracy.Finally, they have developed an early diagnosis of silicosis and prediction of experimental system. As an open experimental system, using a convenient expansion of programming languages (Visual C++), provides a future-oriented experimental environment of silicosis diagnosis and predict. The system facilitates the computer-aided diagnosis and prediction of the theory of silicosis research implementation.