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LungNet:Integrating CNN with channel attention and multi-scale transformer
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作者 王海滨 刘丽 《中国体视学与图像分析》 2023年第1期56-63,共8页
The SARS-CoV-2 virus has caused various health problems worldwide,including coughing and wheezing.Computed tomography(CT)imaging of lungs can help to determine the presence and location of disease.However,manually eva... The SARS-CoV-2 virus has caused various health problems worldwide,including coughing and wheezing.Computed tomography(CT)imaging of lungs can help to determine the presence and location of disease.However,manually evaluating large numbers of CT images by healthcare professionals places strict demands on their expertise.Our team developed a LungNet system to analyze CT images with the goal of detecting the presence of disease,characterizing the type of lesion to aid medical professionals in diagnosis.To evaluate the performance of our model,we conduct experiments on the publicly available SARS-CoV-2 CT scan dataset,and the classification accuracy can reach 98.8%. 展开更多
关键词 medical ct image SARS-CoV-2 virus classification
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