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In order to explore the influence of intelligent imaging diagnosis systems on comprehensive nursing intervention for patients with late-stage lung cancer, the system uses ITK and VTK toolkit to realize image reading, display, image marking, and interactive functions. The optimal threshold method and regional connectivity algorithm were used to segment the lung region, and then, the cavity filling algorithm and repair algorithm were used to repair the lung region. A variable ring filter was used to detect suspected shadows in the lungs. Finally, the classifier proposed in this paper is used to classify benign and malignant. The system has good sensitivity by detecting the images of real patients. 100 patients with advanced lung cancer were randomly divided into control group and nursing intervention group 50 cases each. Patients in the control group received routine radiotherapy and chemotherapy and routine nursing intervention. Patients in the nursing intervention group were given comprehensive nursing intervention on the basis of routine intervention in the control group for 2 consecutive months. Pittsburgh sleep quality index, pain degree, quality of life, and complications after intervention were compared between the 2 groups before and after intervention. The experimental results showed that the sleep quality, pain degree, quality of life, and complications in 2 groups were significantly improved after intervention ( P  < 0.05), and the improvement degree in the nursing intervention group was higher than that in the control group ( P  < 0.05). It is proved that comprehensive nursing intervention has a good effect on improving sleep quality, relieving physical pain, improving the quality of life, and reducing complications of lung cancer patients and can effectively improve the quality of life of lung cancer patients.

Analysis of Lung Imaging Intelligent Diagnosis System for Nursing Intervention of Lung Cancer Patients’ Quality of Life