Application of high-resolution CT images information in complicated infection of lung tumors.

To explore the quality of high-resolution CT images information in the evaluation of pulmonary nodule interface and internal structure of nodules in lung tissue, as well as the value of early diagnosis of lung cancer associated with infection, high-resolution CT images were used as the research object. Through the analysis of the computerized detection and diagnosis (Computer-Aided Diagnosis (CAD)) of lung cancer, the high-resolution CT was further explored in the process of clinical imaging doctors in the diagnosis of lung cancer, and more conditions were created for the application of medical image processing in the early diagnosis of lung cancer. The research results show that CAD can automatically and accurately complete the automatic segmentation of the lung region in the CT image by applying the automatic segmentation algorithm for a series of processing and analysis of the CT image, that is, generating high-resolution CT images. It can enhance the pulmonary nodules in CT images and improve the accuracy of lung nodule detection, which is of great value in the diagnosis of early lung cancer. CAD diagnosis of lung lesions based on high-resolution CT images is studied, which can provide reference for imaging physicians to diagnose early lung cancer. However, in the automatic identification of benign and malignant lesions in the lungs, it is necessary to further improve the analysis function of similar nodules, which will be an important step for humans in the diagnosis and treatment of diseases.