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Journal Abstract Search

970 related items for PubMed ID: 29573583

  • 1.
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  • 2. 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]

  • 3. Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method.
    Zhou X, Takayama R, Wang S, Hara T, Fujita H.
    Med Phys; 2017 Oct; 44(10):5221-5233. PubMed ID: 28730602
    [Abstract] [Full Text] [Related]

  • 4. 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]

  • 5. 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; 12(3):399-411. PubMed ID: 27885540
    [Abstract] [Full Text] [Related]

  • 6. Vessel segmentation from volumetric images: a multi-scale double-pathway network with class-balanced loss at the voxel level.
    Chen Y, Fan S, Chen Y, Che C, Cao X, He X, Song X, Zhao F.
    Med Phys; 2021 Jul; 48(7):3804-3814. PubMed ID: 33969487
    [Abstract] [Full Text] [Related]

  • 7. Automatic Segmentation of Multiple Organs on 3D CT Images by Using Deep Learning Approaches.
    Zhou X.
    Adv Exp Med Biol; 2020 Jul; 1213():135-147. PubMed ID: 32030668
    [Abstract] [Full Text] [Related]

  • 8. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.
    Tong N, Gou S, Yang S, Ruan D, Sheng K.
    Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285
    [Abstract] [Full Text] [Related]

  • 9. Learning normalized inputs for iterative estimation in medical image segmentation.
    Drozdzal M, Chartrand G, Vorontsov E, Shakeri M, Di Jorio L, Tang A, Romero A, Bengio Y, Pal C, Kadoury S.
    Med Image Anal; 2018 Feb; 44():1-13. PubMed ID: 29169029
    [Abstract] [Full Text] [Related]

  • 10. Liver tissue segmentation in multiphase CT scans using cascaded convolutional neural networks.
    Ouhmich F, Agnus V, Noblet V, Heitz F, Pessaux P.
    Int J Comput Assist Radiol Surg; 2019 Aug; 14(8):1275-1284. PubMed ID: 31041697
    [Abstract] [Full Text] [Related]

  • 11. Automatic localization of solid organs on 3D CT images by a collaborative majority voting decision based on ensemble learning.
    Zhou X, Wang S, Chen H, Hara T, Yokoyama R, Kanematsu M, Fujita H.
    Comput Med Imaging Graph; 2012 Jun; 36(4):304-13. PubMed ID: 22421130
    [Abstract] [Full Text] [Related]

  • 12. Segmentation of liver tumors with abdominal computed tomography using fully convolutional networks.
    Chen CI, Lu NH, Huang YH, Liu KY, Hsu SY, Matsushima A, Wang YM, Chen TB.
    J Xray Sci Technol; 2022 Jun; 30(5):953-966. PubMed ID: 35754254
    [Abstract] [Full Text] [Related]

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  • 14. Abdominal artery segmentation method from CT volumes using fully convolutional neural network.
    Oda M, Roth HR, Kitasaka T, Misawa K, Fujiwara M, Mori K.
    Int J Comput Assist Radiol Surg; 2019 Dec; 14(12):2069-2081. PubMed ID: 31493112
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  • 16. Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks.
    Ibragimov B, Xing L.
    Med Phys; 2017 Feb; 44(2):547-557. PubMed ID: 28205307
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