Abstract
This study was to evaluate the diagnostic value of deep learning-optimized chest CT in the patients with lung cancer. 90 patients who were diagnosed with lung cancer by surgery or puncture in hospital were selected as the research subjects. The Mask Region Convolutional Neural Network (Mask-RCNN) model was a typical end-to-end image segmentation model, and Dual Path Network (DPN) was used in nodule detection. The results showed that the accuracy of DPN algorithm model in detecting lung lesions in lung cancer patients was 88.74%, the accuracy of CT diagnosis of lung cancer was 88.37%, the sensitivity was 82.91%, and the specificity was 87.43%. Deep learning-based CT examination combined with serum tumor detection, factoring into Neurospecific enolase (N S E), cytokeratin 19 fragment (CYFRA21), Carcinoembryonic antigen (CEA), and squamous cell carcinoma (SCC) antigen, improved the accuracy to 97.94%, the sensitivity to 98.12%, and the specificity to 100%, all showing significant differences (P < 0.05). In conclusion, this study provides a scientific basis for improving the diagnostic efficiency of CT imaging in lung cancer and theoretical support for subsequent lung cancer diagnosis and treatment.
Highlights
With the witness of the rapid development of economy, culture, and technology in Chinese society, every Chinese has a genuine sense of joy
Stochastic gradient descent (SGD) training network was utilized in training with iteration times, momentum, learning rate, batch size, and weight decay being 400, 0.78, 0.000098, 3.5, and 0.000098, respectively
The results showed that loss function converged after 360 iterations
Summary
With the witness of the rapid development of economy, culture, and technology in Chinese society, every Chinese has a genuine sense of joy. The impact of the changes in the incidence of lung diseases is the most significant. The incidence of multiple lung disease is enhanced, especially lung cancer [1,2,3]. Among that of various cancer diseases, the incidence and mortality of lung cancer are both at high levels with the rapidly growing trend year by year. Lung cancer is imperceptible because of no other specific clinical manifestations. Some significant symptoms (fever, hemoptysis, and short breath) reveal that patients suffer from the diseases at middle or advanced phases. For these patients, the optimal treatment time is missed with poor prognosis [5, 6]. Early diagnosis and early treatment are of great significance in the prognosis of lung cancer patients
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