Three-dimensional analysis of pulmonary nodules using thin slice helical CT data: automated nodule classification and estimation of malignancy

被引：0
|
作者：
Murao, K [1 ]
Awai, K [1 ]
Ozawa, A [1 ]
Yamanaka, T [1 ]
Komi, M [1 ]
Hori, S [1 ]
机构：
[1] Fujitsu Ltd, Mihama Ku, Chiba 2618588, Japan
来源：
CARS 2002: COMPUTER ASSISTED RADIOLOGY AND SURGERY, PROCEEDINGS | 2002年
关键词：
pulmonary nodule; lung cancer; malignancy;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
引用
收藏
页码：1099 / 1099
页数：1
相关论文
共 50 条
  • [41] Three-dimensional computer-aided diagnosis schemes for classification of benign and malignant pulmonary nodules
    Kawata, Y
    Niki, N
    Ohmatsu, H
    Kusumoto, M
    Kakinuma, R
    Mori, K
    Nishiyama, H
    Eguchi, K
    Kaneko, M
    Moriyama, N
    CARS 2002: COMPUTER ASSISTED RADIOLOGY AND SURGERY, PROCEEDINGS, 2002, : 764 - 769
  • [42] Three-dimensional analysis of ground glass opacities from helical CT scans
    Reeves, AP
    Kostis, WJ
    Yankelevitz, DF
    Henschke, CI
    RADIOLOGY, 2000, 217 : 384 - 384
  • [43] Hybrid Scheme for Automated Classification of Pulmonary Nodules Using PET/CT Images and Patient Information
    Yamada, Ayumi
    Teramoto, Atsushi
    Hoshi, Masato
    Toyama, Hiroshi
    Imaizumi, Kazuyoshi
    Saito, Kuniaki
    Fujita, Hiroshi
    APPLIED SCIENCES-BASEL, 2020, 10 (12):
  • [44] Segmentation of pulmonary nodules in three-dimensional CT images by use of a spiral-scanning technique
    Wang, Jiahui
    Engelmann, Roger
    Li, Qiang
    MEDICAL PHYSICS, 2007, 34 (12) : 4678 - 4689
  • [45] Classification of lung nodules in CT scans using three-dimensional deep convolutional neural networks with a checkpoint ensemble method
    Jung, Hwejin
    Kim, Bumsoo
    Lee, Inyeop
    Lee, Junhyun
    Kang, Jaewoo
    BMC MEDICAL IMAGING, 2018, 18
  • [46] Volumetric segmentation of small pulmonary nodules on three-dimensional thin-section computed tomography
    Kido, S
    Tachibana, R
    RADIOLOGY, 2001, 221 : 204 - 205
  • [47] Classification of lung nodules in CT scans using three-dimensional deep convolutional neural networks with a checkpoint ensemble method
    Hwejin Jung
    Bumsoo Kim
    Inyeop Lee
    Junhyun Lee
    Jaewoo Kang
    BMC Medical Imaging, 18
  • [48] Detection of Pulmonary Nodules CT Images Combined with Two-Dimensional and Three-Dimensional Convolution Neural Networks
    Miao Guang
    Li Chaofeng
    LASER & OPTOELECTRONICS PROGRESS, 2018, 55 (05)
  • [49] Classification of the colonic splenic flexure based on three-dimensional CT analysis
    Kawai, K.
    Nozawa, H.
    Hata, K.
    Tanaka, T.
    Nishikawa, T.
    Sasaki, K.
    Ishihara, S.
    BJS OPEN, 2021, 5 (01):
  • [50] Application value of CT three-dimensional reconstruction technology in the identification of benign and malignant lung nodules and the characteristics of nodule distribution
    Guanghai Ji
    Fei Liu
    Zhiqiang Chen
    Jie Peng
    Hao Deng
    Sheng Xiao
    Yun Li
    BMC Medical Imaging, 25 (1)
12345