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MeSH:(Anthracosis/diagnostic imaging*)

2.Application of a light-weighted convolutional neural network for automatic recognition of coal workers' pneumoconiosis in the early stage.

Feng Tao CUI ; Yan WANG ; Xin Ping DING ; Yu Long YAO ; Bing LI ; Fu Hai SHEN

Chinese Journal of Industrial Hygiene and Occupational Diseases 2023;41(3):177-182

3.The analysis of consistency between digital radiography and high-kV chest radiographs in diagnosis pneumoconiosis.

Jun-Qiang CHEN ; Zhao-Qiang JIANG ; Yun XIAO ; Yun-Wu ZHAO ; Xing ZHANG

Chinese Journal of Industrial Hygiene and Occupational Diseases 2012;30(1):8-12

4.Effects of image post-processing parameters on digital radiography chest radiograph for the diagnosis of pneumoconiosis.

Jun-Qiang CHEN ; Zhao-Qiang JIANG ; Bin ZHOU ; Qiang ZHU ; Bin LIU ; Xing ZHANG

Chinese Journal of Industrial Hygiene and Occupational Diseases 2012;30(1):3-7

6.Diagnostic value and clinical application of CT/HRCT for coal workers' pneumoconiosis with large opacities.

Pei-cheng LIU ; Han-xin SU ; Patiguli ; Gui-ping CAI ; Xue-ru AI ; Chun WU ; Yu-ling WANG ; Shao-qun MA ; Awaguli

Chinese Journal of Industrial Hygiene and Occupational Diseases 2007;25(6):350-353

8.Exploration of the early detection of lung parenchyma micronodules, nodule coalescence and emphysema by CT and HRCT in coal miners with and without coal-worker's pneumoconiosis evidence.

Hou-Mao REN ; Jing-Cai XING ; Li-Juan YANG ; Wen-Hui HAN ; Wan-Jun YI ; Wei-Hong CHEN

Chinese Journal of Industrial Hygiene and Occupational Diseases 2012;30(1):13-16

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