An image segmentation method of lung lymphatic tumors based on PET-CT images

To address the problem from lymphatic tumor segmentation from PET-CT images, this paper presents an image segmentation method based on pulse-coupled neural network (PCNN). PET-CT image detection can provide more detailed tumor information for later diagnosis and treatment, while our adjustable fire-controlled MSPCNN model (AFC-MSPCNN) can segment lung tumors effectively. Related experiment results show that our proposed method can improve the image segmentation accuracy than other competitive methods.