The application progress of Convolutional Neural Networks (CNN) in lung nodule diagnosis

Abstract

With the development of computers, machine learning continues to be widely used in various fields. And there are many application scenarios in the field of medicine. Among these, the broadest one is the field of medical image analysis. Medical image has the characteristics of huge data, excessive noise, and recognition difficulty. And the most difficult one is the analysis of lung medical images. Lung cancer has a higher incidence rate and mortality rate than other cancers. According to the National Cancer Center, about 127,070 people died from lung cancer in 2023, making it the highest death rate in the United States. Therefore, early detection of malignant pulmonary nodules has become crucial in the field of medical imaging. The medical imaging's inadequacies are most noticeable in the pictures of malignant pulmonary nodules, which are difficult for a doctor to identify with their naked eyes. However, pre-processing, segmentation difficulties, and poor fitting impact are the drawbacks of classical machine learning. As a result, we must create fresh approaches to these issues.