摘要
The aim of this article is to review recent progress in the application of artificial intelligence to chest medical image analysis.The lungs,bone,and mediastinum were included in terms of anatomy,while X-ray and computed tomography(CT),with and without contrast enhancement,were considered regarding imaging modalities.Four key components of deep learning were summarized,namely,network architectures,learning strategies,optimiza-tion methods,and vision tasks.Disease-specific applications were discussed in detail with respect to the dimen-sion of the data input,network architecture,and modality:lung cancer,pneumonia,tuberculosis,pulmonary embolism,chronic obstructive pulmonary disease,and interstitial lung disease for lung;traumatic fractures,os-teoporosis,osteoporotic fractures,and bone metastases for bone;and coronary artery calcification and aortic dissection for vascular diseases.Finally,five promising research directions and possible solutions were presented for future work.
基金
supported in part by the Beijing Municipal Sci-ence and Technology Planning Project(Grant Nos.Z201100005620008,Z201100005620002 and Z211100003521009)
projects of National Natural Science Foundation of China(Grant Nos.82072005 and 81971616)
Science and Technology Commission of Shanghai Xuhui District Municipality(Grant No.2020-010).