首页> International journal of computer assisted radiology and surgery> A semantic fidelity interpretable-assisted decision model for lung nodule classification.

A semantic fidelity interpretable-assisted decision model for lung nodule classification.

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第一作者： Xiangbing,Zhan

第一单位： State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025, China.

作者： Xiangbing,Zhan ^[1] ; Huiyun,Long ^[2] ; Fangfang,Gou ^[3] ; Jia,Wu ^[4]

作者单位： State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025, China. ^[1] State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025, China. long_huiyun@163.com. ^[2] State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025, China. gff8221@163.com. ^[3] State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025, China. jiawu5110@163.com.;Research Center for Artificial Intelligence, Monash University, Melbourne, Clayton, VIC, 3800, Australia. jiawu5110@163.com. ^[4]

关键词 Capsule networks Interpretability Lung nodule Multi-class classification Semantic fidelity

主题词人类(Humans);语义学(Semantics);体层摄影术, X线计算机(Tomography, X-Ray Computed);肺肿瘤(Lung Neoplasms);肺(Lung);孤立性肺结节(Solitary Pulmonary Nodule);放射摄影影像解释, 计算机辅助(Radiographic Image Interpretation, Computer-Assisted)

DOI 10.1007/s11548-023-03043-5

PMID 38141069

发布时间 2024-03-29

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