Fast classification of benign and malignant solitary pulmonary nodules in CT image

被引：0
|
作者：
Liu, Lu [1 ]
Liu, Wan-Yu [1 ]
Chu, Chun-Yu [2 ]
Wu, Jun [3 ]
Zhou, Yang [3 ]
Zhang, Hong-Xia [3 ]
Bao, Jie [1 ]
机构：
[1] HIT-INSA Sino-French Research Center for Biomedical Imaging, Harbin Institute of Technology, Harbin 150001, China
[2] School of Automation, Harbin University of Science and Technology, Harbin 150080, China
[3] The Tumor Hospital of Harbin Medical University, Harbin 150081, China
来源：
Guangxue Jingmi Gongcheng/Optics and Precision Engineering | 2009年 / 17卷 / 08期
关键词：
22;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：2060 / 2068
相关论文
共 50 条
  • [41] Joint generative adversarial network model for classification of benign and malignant pulmonary nodules
    Wang G.
    Lin Z.
    Fu Q.
    Wang J.
    Lu G.
    Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2020, 41 (11): : 188 - 197
  • [42] Using radiomics feature to distinguish malignant from benign solitary pulmonary nodules on dual time point PET/CT images
    Chen, Song
    Li, Xuena
    Jeraj, Robert
    Li, Yaming
    JOURNAL OF NUCLEAR MEDICINE, 2021, 62
  • [43] Performance of Ensemble Learning Classifiers on Malignant-Benign Classification of Pulmonary Nodules
    Tartar, Ahmet
    Akan, Aydin
    2014 22ND SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2014, : 722 - 725
  • [44] BiCFormer: Swin Transformer based model for classification of benign and malignant pulmonary nodules
    Zhao, Xiaoping
    Xu, Jingjing
    Lin, Zhichen
    Xue, Xingan
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2024, 35 (07)
  • [45] Automatic Detection and Classification of Solitary Pulmonary Nodules from Lung CT Images
    Mukherjee, Jhilam
    Chakrabarti, Amlan
    Skaikh, Soharab Hossain
    Kar, Madhuchanda
    2014 FOURTH INTERNATIONAL CONFERENCE OF EMERGING APPLICATIONS OF INFORMATION TECHNOLOGY (EAIT), 2014, : 294 - 299
  • [46] Prediction efficacy of feature classification of solitary pulmonary nodules based on CT radiomics
    Xu, Qing-qing
    Shan, Wen-li
    Zhu, Yan
    Huang, Chen-cui
    Bao, Si-yu
    Guo, Li-li
    EUROPEAN JOURNAL OF RADIOLOGY, 2021, 139
  • [47] The use of quantitative image features to classify solitary pulmonary nodules imaged on CT
    Wyckoff, N
    McNitt-Gray, MF
    Goldin, JG
    Suh, R
    Sayre, JW
    Aberle, DR
    RADIOLOGY, 2000, 217 : 207 - 207
  • [48] Energy spectrum computed tomography improves the differentiation between benign and malignant solitary pulmonary nodules
    Zhao, Jianhong
    Chai, Yanjun
    Zhou, Junlin
    Zhang, Zhuoli
    Wang, Zhiping
    CLINICAL AND INVESTIGATIVE MEDICINE, 2019, 42 (03): : E40 - E46
  • [49] Analysis of the Discriminative Methods for Diagnosis of Benign and Malignant Solitary Pulmonary Nodules Based on Serum Markers
    Wang, Wanping
    Liu, Mingyue
    Wang, Jing
    Tian, Rui
    Dong, Junqiang
    Liu, Qi
    Zhao, Xianping
    Wang, Yuanfang
    ONCOLOGY RESEARCH AND TREATMENT, 2014, 37 (12) : 740 - 746
  • [50] Automated computerized scheme for distinction between benign and malignant solitary pulmonary nodules on chest images
    Aoyama, M
    Li, Q
    Katsuragawa, S
    MacMahon, H
    Doi, K
    MEDICAL PHYSICS, 2002, 29 (05) : 701 - 708
12345