Computer-aided detection in chest radiography based on artificial intelligence: a survey

被引:217
作者
Qin, Chunli [1 ,2 ]
Yao, Demin [1 ,2 ]
Shi, Yonghong [1 ,2 ]
Song, Zhijian [1 ,2 ]
机构
[1] Fudan Univ, Sch Basic Med Sci, Digital Med Res Ctr, Shanghai, Peoples R China
[2] Shanghai Key Lab Med Imaging Comp & Comp Assisted, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Artificial intelligence; Computer-aided detection; Chest radiography; Disease classification; IMAGE FEATURE ANALYSIS; ACTIVE SHAPE MODEL; LUNG NODULES; DIGITAL RADIOGRAPHY; BONE SUPPRESSION; PULMONARY TUBERCULOSIS; INTERSTITIAL DISEASE; AUTOMATIC DETECTION; DIAGNOSTIC SCHEME; SEGMENTATION;
D O I
10.1186/s12938-018-0544-y
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
As the most common examination tool in medical practice, chest radiography has important clinical value in the diagnosis of disease. Thus, the automatic detection of chest disease based on chest radiography has become one of the hot topics in medical imaging research. Based on the clinical applications, the study conducts a comprehensive survey on computer-aided detection (CAD) systems, and especially focuses on the artificial intelligence technology applied in chest radiography. The paper presents several common chest X-ray datasets and briefly introduces general image preprocessing procedures, such as contrast enhancement and segmentation, and bone suppression techniques that are applied to chest radiography. Then, the CAD system in the detection of specific disease (pulmonary nodules, tuberculosis, and interstitial lung diseases) and multiple diseases is described, focusing on the basic principles of the algorithm, the data used in the study, the evaluation measures, and the results. Finally, the paper summarizes the CAD system in chest radiography based on artificial intelligence and discusses the existing problems and trends.
引用
收藏
页数:23
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