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基于改进CNN的低剂量CT图像肺结节自动检测 岳晴.pdf


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DOI:10.1189 : ; ;cascade-rcnn;3DCNN;LUNA16
中图法分类号
 TP391
 
Automatic Detection of Pulmonary Nodules in Low-dose CT Images Based on Improved CNN
YUE Qing1,YIN Jian-yu2and WANG Sheng-sheng2
1School of Computer Science,Jilin Normal University,Siping,Jilin 136000,China
2College of Computer Science and Technology,Jilin University,Changchun 130000,China
 
Abstract With air pollution getting worse and worse,lung cancer has become one of the malignant tumors with the fastest in-
creasing morbidity and mortality rate,which seriously endangers people's life and health.The early stage of lung cancer is mainly
in the form of pulmonary nodules.If the early stage of lung cancer can be detected and treated in time,the treatment effect of lung
cancer will be improved.Low-dose spiral CT is widely used in the diagnosis of pulmonary nodules because of its characteristics of
fast acquisition speed,low cost and low radiation.At present,CT image diagnosis mostly adopts the traditional manual diagnosis
and CAD system diagnosis,but these two methods have the disadvantages of low accuracy and poor generalization.In view of the
above problems,this paper takes the detection of pulmonary nodules in the field of medical assisted diagnosis as the re

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