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首页> Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society> Fast and fully-automated detection and segmentation of pulmonary nodules in thoracic CT scans using deep convolutional neural networks.

Fast and fully-automated detection and segmentation of pulmonary nodules in thoracic CT scans using deep convolutional neural networks.

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第一作者： Xia,Huang

第一单位： Department of Metallurgical, Materials, and Biomedical Engineering, University of Texas at El Paso, El Paso, TX, 79968, United States.

作者： Xia,Huang ^[1] ; Wenqing,Sun ^[2] ; Tzu-Liang Bill,Tseng ^[3] ; Chunqiang,Li ^[4] ; Wei,Qian ^[5]

作者单位： Department of Metallurgical, Materials, and Biomedical Engineering, University of Texas at El Paso, El Paso, TX, 79968, United States. ^[1] Department of Electrical and Computer Engineering, University of Texas at El Paso, El Paso, TX, 79968, United States. ^[2] Department of Industrial, Manufacturing, and Systems Engineering, University of Texas at El Paso, El Paso, TX, 79968, United States. ^[3] Department of Physics, University of Texas at El Paso, El Paso, TX, 79968, United States. Electronic address: cli@utep.edu. ^[4] Department of Electrical and Computer Engineering, University of Texas at El Paso, El Paso, TX, 79968, United States. Electronic address: wqian@utep.edu. ^[5]

关键词 Computer aided diagnosis Convolutional neural networks Faster regional-CNN Fully convolutional neural network (FCN)Pulmonary nodule detection and segmentation

主题词数据库, 事实型(Databases, Factual);诊断, 计算机辅助(Diagnosis, Computer-Assisted);女(雌)性(Female);人类(Humans);肺肿瘤(Lung Neoplasms);男(雄)性(Male);放射摄影影像解释, 计算机辅助(Radiographic Image Interpretation, Computer-Assisted);体层摄影术, X线计算机(Tomography, X-Ray Computed)

DOI 10.1016/j.compmedimag.2019.02.003

PMID 30954678

发布时间 2020-07-09

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Computerized medical imaging and graphics

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