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Research Article

Station number assignment to abdominal lymph node for assisting gastric cancer surgery

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Pages 357-362 | Received 11 Sep 2020, Accepted 07 Oct 2020, Published online: 30 Oct 2020

References

  • Altun HC, Chlebus G, Jacobs C, Meine H, van Ginneken B, Hahn HK. 2020. Feasibility of end-to-end trainable two-stage U-Net for detection of axillary lymph nodes in contrast-enhanced CT based on sparse annotations. Proc SPIE. 11314:113141C.
  • Bouget D, Jørgensen A, Kiss G, Leira HO, Langø T. 2019. Semantic segmentation and detection of mediastinal lymph nodes and anatomical structures in CT data for lung cancer staging. Int J CARS. 14:977–986.
  • Degiuli M, De Manzoni G, Di Leo A, D’Ugo D, Galasso E, Marrelli D, Petrioli R, Polom K, Roviello F, Santullo F, et al. 2016. Gastric cancer: current status of lymph node dissection. World J Gastroenterol. 22:2875–2893.
  • Feuerstein M, Glocker B, Kitasaka T, Nakamura Y, Iwano S, Mori K. 2012. Mediastinal atlas creation from 3-D chest computed tomography images: application to automated detection and station mapping of lymph nodes. Med Image Anal. 16:63–74.
  • Glocker B, Komodakis N, Tziritas G, Navab N, Paragios N. 2008. Dense image registration through MRFs and efficient linear programming. Med Image Anal. 12:731–741. doi:10.1016/j.media.2008.03.006.
  • Japanese Gastric Cancer Association. 2011. Japanese classification of gastric carcinoma: 3rd English edition. Gastric Cancer. 14:101–112. doi:10.1007/s10120-011-0041-5
  • Japanese Gastric Cancer Association. 2017. Japanese gastric cancer treatment guidelines 2014 (ver. 4). Gastric Cancer. 20:1–19.
  • Liu J, Hoffman J, Zhao J, Yao J, Lu L, Kim L, Turkbey EB, Summers RM. 2016. Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest. Med Phys. 43:4362–4374.
  • Lu K, Taeprasartsit P, Bascom R, Mahraj RPM, Higgins WE. 2011. Automatic definition of the central-chest lymph-node stations. Int J CARS. 6:539–555. doi:10.1007/s11548-011-0547-7.
  • Nakamura Y, Nimura Y, Oda M, Kitasaka T, Furukawa K, Goto H, Fujiwara M, Misawa K, Mori K. 2016. Ensemble lymph node detection from CT volumes combining local intensity structure analysis approach and appearance learning approach. Proc SPIE. 9785:97852X-1–97852X–7.
  • Roth HR, Lu L, Seff A, Cherry KM, Hoffman J, Wang S, Liu J, Turkbey E, Summers RM. 2014. A new 2.5D representation for lymph node detection using random sets of deep convolutional neural network observations. Proceeding of MICCAI 2014. LNCS. 8673:520–527.
  • Saito T, Toriwaki J. 1994. New algorithms for Euclidean distance transformation of an n-dimensional digitized picture with applications. Pattern Recognit. 27:1151–1565. doi:10.1016/0031-3203(94)90133-3.
  • Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. 2015. Global cancer statistics, 2012. CA Cancer J Clin. 65:87–108.
  • Yan K, Wang X, Lu L, Summers RM. 2018. DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning. Journal of Medical Imaging. 5(3):036501. doi:10.1117/1.JMI.5.3.036501.

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