These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

2215 related items for PubMed ID: 31356688

  • 1. Automatic liver segmentation by integrating fully convolutional networks into active contour models.
    Guo X, Schwartz LH, Zhao B.
    Med Phys; 2019 Oct; 46(10):4455-4469. PubMed ID: 31356688
    [Abstract] [Full Text] [Related]

  • 2. Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model.
    Hu Y, Guo Y, Wang Y, Yu J, Li J, Zhou S, Chang C.
    Med Phys; 2019 Jan; 46(1):215-228. PubMed ID: 30374980
    [Abstract] [Full Text] [Related]

  • 3.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 4.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 5.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 6. Esophagus segmentation in CT via 3D fully convolutional neural network and random walk.
    Fechter T, Adebahr S, Baltas D, Ben Ayed I, Desrosiers C, Dolz J.
    Med Phys; 2017 Dec; 44(12):6341-6352. PubMed ID: 28940372
    [Abstract] [Full Text] [Related]

  • 7. Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.
    Roth HR, Lu L, Lay N, Harrison AP, Farag A, Sohn A, Summers RM.
    Med Image Anal; 2018 Apr; 45():94-107. PubMed ID: 29427897
    [Abstract] [Full Text] [Related]

  • 8.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 9. Adaptive Estimation of Active Contour Parameters Using Convolutional Neural Networks and Texture Analysis.
    Hoogi A, Subramaniam A, Veerapaneni R, Rubin DL.
    IEEE Trans Med Imaging; 2017 Mar; 36(3):781-791. PubMed ID: 28113927
    [Abstract] [Full Text] [Related]

  • 10. Toward reliable automatic liver and tumor segmentation using convolutional neural network based on 2.5D models.
    Wardhana G, Naghibi H, Sirmacek B, Abayazid M.
    Int J Comput Assist Radiol Surg; 2021 Jan; 16(1):41-51. PubMed ID: 33219906
    [Abstract] [Full Text] [Related]

  • 11. Superpixel-based and boundary-sensitive convolutional neural network for automated liver segmentation.
    Qin W, Wu J, Han F, Yuan Y, Zhao W, Ibragimov B, Gu J, Xing L.
    Phys Med Biol; 2018 May 04; 63(9):095017. PubMed ID: 29633960
    [Abstract] [Full Text] [Related]

  • 12.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 13.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 14.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 15. An iterative multi-path fully convolutional neural network for automatic cardiac segmentation in cine MR images.
    Ma Z, Wu X, Wang X, Song Q, Yin Y, Cao K, Wang Y, Zhou J.
    Med Phys; 2019 Dec 04; 46(12):5652-5665. PubMed ID: 31605627
    [Abstract] [Full Text] [Related]

  • 16. Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model.
    He B, Huang C, Sharp G, Zhou S, Hu Q, Fang C, Fan Y, Jia F.
    Med Phys; 2016 May 04; 43(5):2421. PubMed ID: 27147353
    [Abstract] [Full Text] [Related]

  • 17. Automatic 3D CT liver segmentation based on fast global minimization of probabilistic active contour.
    Jin R, Wang M, Xu L, Lu J, Song E, Ma G.
    Med Phys; 2023 Apr 04; 50(4):2100-2120. PubMed ID: 36413182
    [Abstract] [Full Text] [Related]

  • 18. Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.
    Hu P, Wu F, Peng J, Bao Y, Chen F, Kong D.
    Int J Comput Assist Radiol Surg; 2017 Mar 04; 12(3):399-411. PubMed ID: 27885540
    [Abstract] [Full Text] [Related]

  • 19.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 20.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 111.