Lv Linying, Liu Xiabi, Zhou Chunwu, Zhao Xinming and Zhao Yanfeng Pages 20 - 31 ( 12 )
The automatic detection of Ground-Glass Opacity (GGO) in lung CT images is very useful for early diagnosis of lung cancers. In this paper, we present a study of previous GGO detection methods and summarize a common algorithm framework, which includes three components: preprocessing, candidate extraction and GGO identification. For each component, we discuss the main methods. Also we further describe the evaluation criterion and provide a comparison of the performance of the existing approaches.
Lung CT images, Imaging signs, GGO nodule, GGO detection, Medical imaging, Computer aided detection (CAD).
Beijing Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing 100081