Abstract
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.
Keywords: Lung CT images, Imaging signs, GGO nodule, GGO detection, Medical imaging, Computer aided detection (CAD).
Graphical Abstract
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