Lung Nodule Segmentation Using EM Algorithm
Yiming Qian, Weng Guirong · 2014
Lung disease is often performed as nodules. Pulmonary nodule is one of important symbols of lung disease. Characteristics of pulmonary nodules always indicate the nature of lung disease. Detection of pulmonary nodules has great significance in diagnosing lung cancer. Study of pulmonary nodules is now a hot research. CT is a new type of medical imaging equipment with a high density resolution and adequate image information. But to detect small pulmonary nodes, radiologists need to read a lot of images. It could easily lead to misdiagnosis and miss-diagnosis. This paper uses EM algorithm in CT images for the lung nodule detection and segmentation. The application shows that the method of this paper is to improve the early detection rate of lung cancer nodules and one of the effective methods using computer-aided analysis of lung nodules. The algorithm used is simple, effective and practical.