A Method of Chest Film Segmentation Based on Minimum Error Threshold Method

Abstract

In recent years, due to irregular life schedule and environmental pollution, the incidence rate and mortality of lung cancer have greatly increased. However, early detection and treatment can significantly reduce mortality. In the diagnosis of lung cancer, X-ray plays a key role. With the wide application of artificial intelligence, intelligent analysis of medical images has also ushered in a new breakthrough. In the intelligent analysis of medical images, image segmentation is an extremely critical link. This paper mainly introduces an image segmentation method about minimum error threshold segmentation, which provides an efficient and convenient method for medical image segmentation. This method can effectively extract the target lung region, avoid obvious over-segmentation and interference of stomach air region, and eliminate cavities and noise points, to obtain more accurate lung segmentation effect. Various reasons have led to the rapid rise of the incidence rate and mortality of lung cancer. Lung cancer will become one of the most threatening diseases to mankind in the 21st century. People should pay more attention to lung cancer related issues, realizing the advantages of intelligent analysis of medical images, and pay more attention to this field.