Development and performance evaluation of a deep learning lung nodule detection system

被引：0
|
作者：
Shichiro Katase
Akimichi Ichinose
Mahiro Hayashi
Masanaka Watanabe
Kinka Chin
Yuhei Takeshita
Hisae Shiga
Hidekatsu Tateishi
Shiro Onozawa
Yuya Shirakawa
Koji Yamashita
Jun Shudo
Keigo Nakamura
Akihito Nakanishi
Kazunori Kuroki
Kenichi Yokoyama
机构：
[1] Kyorin University,Department of Radiology, Faculty of Medicine
[2] Fujifilm Corporation,Imaging Technology Center, ICT Strategy Division
[3] Kyorin University Hospital,Department of Radiology
来源：
BMC Medical Imaging | / 22卷
关键词：
Artificial intelligence; Lung nodule; Computer aided detection; Deep learning;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [1] Development and performance evaluation of a deep learning lung nodule detection system
    Katase, Shichiro
    Ichinose, Akimichi
    Hayashi, Mahiro
    Watanabe, Masanaka
    Chin, Kinka
    Takeshita, Yuhei
    Shiga, Hisae
    Tateishi, Hidekatsu
    Onozawa, Shiro
    Shirakawa, Yuya
    Yamashita, Koji
    Shudo, Jun
    Nakamura, Keigo
    Nakanishi, Akihito
    Kuroki, Kazunori
    Yokoyama, Kenichi
    BMC MEDICAL IMAGING, 2022, 22 (01)
  • [2] Deep Learning System for Lung Nodule Detection
    Yang, D.
    Powell, C.
    Bai, C.
    Hu, J.
    Lu, S.
    Wang, N.
    JOURNAL OF THORACIC ONCOLOGY, 2017, 12 (11) : S2329 - S2329
  • [3] CAD system for lung nodule detection using deep learning with CNN
    Manickavasagam, R.
    Selvan, S.
    Selvan, Mary
    MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 2022, 60 (01) : 221 - 228
  • [4] CAD system for lung nodule detection using deep learning with CNN
    R. Manickavasagam
    S. Selvan
    Mary Selvan
    Medical & Biological Engineering & Computing, 2022, 60 : 221 - 228
  • [5] Lung Nodule Detection via Deep Reinforcement Learning
    Ali, Issa
    Hart, Gregory R.
    Gunabushanam, Gowthaman
    Liang, Ying
    Muhammad, Wazir
    Nartowt, Bradley
    Kane, Michael
    Ma, Xiaomei
    Deng, Jun
    FRONTIERS IN ONCOLOGY, 2018, 8
  • [6] Performance of a deep learning-based lung nodule detection system as an alternative reader in a Chinese lung cancer screening program
    Cui, Xiaonan
    Zheng, Sunyi
    Heuvelmans, Marjolein A.
    Du, Yihui
    Sidorenkov, Grigory
    Fan, Shuxuan
    Li, Yanju
    Xie, Yongsheng
    Zhu, Zhongyuan
    Dorrius, Monique D.
    Zhao, Yingru
    Veldhuis, Raymond N. J.
    de Bock, Geertruida H.
    Oudkerk, Matthijs
    van Ooijen, Peter M. A.
    Vliegenthart, Rozemarijn
    Ye, Zhaoxiang
    EUROPEAN JOURNAL OF RADIOLOGY, 2022, 146
  • [7] Lung parenchyma segmentation and nodule detection using deep learning
    Nandeesh, G. S.
    Nagabushanam, M.
    Pramodkumar, S.
    Nandini, S.
    JOURNAL OF OPTICS-INDIA, 2024, 53 (01): : 635 - 642
  • [8] Lung parenchyma segmentation and nodule detection using deep learning
    G. S. Nandeesh
    M. Nagabushanam
    S. Pramodkumar
    S. Nandini
    Journal of Optics, 2024, 53 : 635 - 642
  • [9] Effect of CT reconstruction settings on the performance of a deep learning based lung nodule CAD system
    Blazis, Stephan P.
    Dickerscheid, Dennis B. M.
    Linsen, Philip V. M.
    Jarnalo, Carine O. Martins
    EUROPEAN JOURNAL OF RADIOLOGY, 2021, 136
  • [10] Quantifying the incremental value of deep learning: Application to lung nodule detection
    Warsavage, Theodore, Jr.
    Xing, Fuyong
    Baron, Anna E.
    Feser, William J.
    Hirsch, Erin
    Miller, York E.
    Malkoski, Stephen
    Wolf, Holly J.
    Wilson, David O.
    Ghosh, Debashis
    PLOS ONE, 2020, 15 (04):
12345