结核(地质)
计算机科学
放射科
模式
特征(语言学)
肺孤立结节
肺
医学
人工智能
计算机断层摄影术
内科学
哲学
社会学
古生物学
生物
语言学
社会科学
作者
Junjie Zhang,Yong Xia,Hengfei Cui,Yanning Zhang
标识
DOI:10.1016/j.bspc.2018.01.011
摘要
Malignant nodules may be due to primary tumors or a metastasis and, given the importance of diagnosing early primary lung tumors, the detection of pulmonary nodules is critical. Therefore, a lot of research efforts have been devoted to the research on computer-aided detection (CADe) schemes for pulmonary nodule detection. This survey sheds light on what CADe schemes are really implementing to detect pulmonary nodules and which will in turn assist radiologist for better diagnosis. This paper provides a systematic depiction of both feature engineering- and deep learning-based CADe schemes, including the categories of pulmonary nodules, modalities of chest medical imaging, commonly used datasets with nodule annotations, and related publications in recent years. A comprehensive comparison and analyses of pulmonary nodule detection schemes proposed in the last three years are also presented.
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