Application of Intelligent Image Processing in Precision Diagnosis of Pulmonary Ground Glass Nodules

Lung cancer is one of the most malignant tumors with high incidence rate and mortality rate. Early diagnosis and clinical intervention is the best method to deal with, which will greatly improve survival rate for lung cancer in five years. In clinic, pulmonary ground glass nodules is closely related to lung cancer. Therfore, the establishment of early screening mechanism of pulmonary ground glass nodules will help to improve the diagnostic ability of lung cancer. The paper constructs an auxiliary analysis tool of pulmonary ground glass nodules by image pattern enhancement, image pattern recognition, deep learning segmentation algorithm, machine learning classification model and other methods. In test, the auxiliary diagnosis accuracy of the intelligent image processing in positive cases has been close to the ability of clinical junior doctors, meanwhile, the average diagnosis time is shortened by 68.51%, which shows that the method has stable calculation and high recall rate, can improve the efficiency of clinical diagnosis, simple the implementation, has practical significance and research value in lung cancer auxiliary screening.