Lung cancer is a disease morbidity and mortality are high， can be divided into small cell lung cancer and non-small cell lung Due to small cell lung cancer and the clinical treatment and prognosis of non-small cell lung cancer are completely different， assist clinicians to identify classification diagnosis has important This paper image segmentation method is utilized to extract the lung cancer lung parenchyma of CT image， and create its gray level co-occurrence matrix and gray level co-occurrence matrix is utilized to extract image texture feature of lung Then texture feature dataset for SPSS pca dimension reduction， generate new data samples， the use of BP neural network， RBF neural network and support vector machine learning algorithm for training The classification results show that the degree of sensitivity and the characteristics of BP neural network classification results can reach above 8 and the coincidence rate is relatively Support vector machine (SVM) classifier classification results followed， RBF used in the classification of the Key words: lung cancer;Gray level co-occurrence matrix;Texture feature;Neural network;Support vector machine (SVM)The pulse signal is the life of the human basic symbol， one of the pulse signal detection in clinical， teaching and scientific research plays a very important Current pulse signal monitoring is using special medical instrument， the instrument is fixed， single function， huge volume， high price， analysis of such problems as In this paper， a pulse signal acquisition and analysis system was designed and The system mainly consists of two parts of hardware and Hardware part using HK - 2000 series integrated pulse sensor complete the pulse signal acquisition and Software part do the login interface with LabVIEW and main form interface， signal acquisition interface by VB programming， VB program to realize the calling through the LabVIEW real-time display and storage of pulse This system friendly interface， simple operation， enhance the function of automatic analysis of traditional medical instruments， has a certain application 采纳我的我的比楼下好
