Automated detection and segmentation of thoracic lymph nodes from CT using 3D foveal fully convolutional neural networks

被引:0
|
作者
Andra-Iza Iuga
Heike Carolus
Anna J. Höink
Tom Brosch
Tobias Klinder
David Maintz
Thorsten Persigehl
Bettina Baeßler
Michael Püsken
机构
[1] University of Cologne,Institute of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Cologne
[2] Philips Research,Institute of Diagnostic and Interventional Radiology
[3] University Hospital Zürich,undefined
来源
关键词
Deep learning; Artificial intelligence; Lymph nodes; Computed tomography; Staging;
D O I
暂无
中图分类号
学科分类号
摘要
引用
下载
收藏
相关论文
共 50 条
  • [1] Automated detection and segmentation of thoracic lymph nodes from CT using 3D foveal fully convolutional neural networks
    Iuga, Andra-Iza
    Carolus, Heike
    Hoeink, Anna J.
    Brosch, Tom
    Klinder, Tobias
    Maintz, David
    Persigehl, Thorsten
    Baessler, Bettina
    Puesken, Michael
    BMC MEDICAL IMAGING, 2021, 21 (01)
  • [2] Automated Detection and Segmentation of Mediastinal and Axillary Lymph Nodes from CT Using Foveal Fully Convolutional Networks
    Carolus, Heike
    Iuga, Andra-Iza
    Brosch, Tom
    Wiemker, Rafael
    Thiele, Frank
    Hoeink, Anna
    Maintz, David
    Puesken, Michael
    Klinder, Tobias
    MEDICAL IMAGING 2020: COMPUTER-AIDED DIAGNOSIS, 2020, 11314
  • [3] Automated localization and segmentation of cervical lymph nodes on contrast-enhanced CT using a 3D foveal fully convolutional neural network
    Rinneburger, Miriam
    Carolus, Heike
    Iuga, Andra-Iza
    Weisthoff, Mathilda
    Lennartz, Simon
    Hokamp, Nils Grosse
    Caldeira, Liliana
    Shahzad, Rahil
    Maintz, David
    Laqua, Fabian Christopher
    Baessler, Bettina
    Klinder, Tobias
    Persigehl, Thorsten
    EUROPEAN RADIOLOGY EXPERIMENTAL, 2023, 7 (01)
  • [4] Automated localization and segmentation of cervical lymph nodes on contrast-enhanced CT using a 3D foveal fully convolutional neural network
    Miriam Rinneburger
    Heike Carolus
    Andra-Iza Iuga
    Mathilda Weisthoff
    Simon Lennartz
    Nils Große Hokamp
    Liliana Caldeira
    Rahil Shahzad
    David Maintz
    Fabian Christopher Laqua
    Bettina Baeßler
    Tobias Klinder
    Thorsten Persigehl
    European Radiology Experimental, 7
  • [5] Fully automated condyle segmentation using 3D convolutional neural networks
    Nayansi Jha
    Taehun Kim
    Sungwon Ham
    Seung-Hak Baek
    Sang-Jin Sung
    Yoon-Ji Kim
    Namkug Kim
    Scientific Reports, 12
  • [6] Fully automated condyle segmentation using 3D convolutional neural networks
    Jha, Nayansi
    Kim, Taehun
    Ham, Sungwon
    Baek, Seung-Hak
    Sung, Sang-Jin
    Kim, Yoon-Ji
    Kim, Namkug
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [7] Ensemble 3D Convolutional Neural Networks for Automated Detection of Diseased Lymph Nodes
    Weisman, Amy
    Kieler, Minnie
    Perlman, Scott
    Jerai, Robert
    Hutchings, Martin
    Kostakoglu, Lale
    Bradshaw, Tyler
    JOURNAL OF NUCLEAR MEDICINE, 2020, 61
  • [8] Fully automated body composition analysis in routine CT imaging using 3D semantic segmentation convolutional neural networks
    Sven Koitka
    Lennard Kroll
    Eugen Malamutmann
    Arzu Oezcelik
    Felix Nensa
    European Radiology, 2021, 31 : 1795 - 1804
  • [9] Fully automated body composition analysis in routine CT imaging using 3D semantic segmentation convolutional neural networks
    Koitka, Sven
    Kroll, Lennard
    Malamutmann, Eugen
    Oezcelik, Arzu
    Nensa, Felix
    EUROPEAN RADIOLOGY, 2021, 31 (04) : 1795 - 1804
  • [10] Fast and fully-automated detection and segmentation of pulmonary nodules in thoracic CT scans using deep convolutional neural networks
    Huang, Xia
    Sun, Wenqing
    Tseng, Tzu-Liang
    Li, Chunqiang
    Qian, Wei
    COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2019, 74 : 25 - 36