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Journal Abstract Search

389 related items for PubMed ID: 36384059

  • 1. A novel multi-atlas segmentation approach under the semi-supervised learning framework: Application to knee cartilage segmentation.
    Chadoulos CG, Tsaopoulos DE, Moustakidis S, Tsakiridis NL, Theocharis JB.
    Comput Methods Programs Biomed; 2022 Dec; 227():107208. PubMed ID: 36384059
    [Abstract] [Full Text] [Related]

  • 2. Dense Multi-Scale Graph Convolutional Network for Knee Joint Cartilage Segmentation.
    Chadoulos C, Tsaopoulos D, Symeonidis A, Moustakidis S, Theocharis J.
    Bioengineering (Basel); 2024 Mar 14; 11(3):. PubMed ID: 38534552
    [Abstract] [Full Text] [Related]

  • 3. Semi-supervised abdominal multi-organ segmentation by object-redrawing.
    Cho MJ, Lee JS.
    Med Phys; 2024 Nov 14; 51(11):8334-8347. PubMed ID: 39167059
    [Abstract] [Full Text] [Related]

  • 4. Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.
    Burton W, Myers C, Rullkoetter P.
    Comput Methods Programs Biomed; 2020 Jun 14; 189():105328. PubMed ID: 31958580
    [Abstract] [Full Text] [Related]

  • 5. Semi-supervised learning framework with shape encoding for neonatal ventricular segmentation from 3D ultrasound.
    Szentimrey Z, Al-Hayali A, de Ribaupierre S, Fenster A, Ukwatta E.
    Med Phys; 2024 Sep 14; 51(9):6134-6148. PubMed ID: 38857570
    [Abstract] [Full Text] [Related]

  • 6. A modality-collaborative convolution and transformer hybrid network for unpaired multi-modal medical image segmentation with limited annotations.
    Liu H, Zhuang Y, Song E, Xu X, Ma G, Cetinkaya C, Hung CC.
    Med Phys; 2023 Sep 14; 50(9):5460-5478. PubMed ID: 36864700
    [Abstract] [Full Text] [Related]

  • 7. Voxel-wise adversarial semi-supervised learning for medical image segmentation.
    Lee CE, Park H, Shin YG, Chung M.
    Comput Biol Med; 2022 Nov 14; 150():106152. PubMed ID: 36208595
    [Abstract] [Full Text] [Related]

  • 8. Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images.
    Liu Y, He Q, Duan H, Shi H, Han A, He Y.
    Sensors (Basel); 2022 Aug 13; 22(16):. PubMed ID: 36015814
    [Abstract] [Full Text] [Related]

  • 9. Automated tibiofemoral joint segmentation based on deeply supervised 2D-3D ensemble U-Net: Data from the Osteoarthritis Initiative.
    Latif MHA, Faye I.
    Artif Intell Med; 2021 Dec 13; 122():102213. PubMed ID: 34823835
    [Abstract] [Full Text] [Related]

  • 10. Automatic knee cartilage and bone segmentation using multi-stage convolutional neural networks: data from the osteoarthritis initiative.
    Gatti AA, Maly MR.
    MAGMA; 2021 Dec 13; 34(6):859-875. PubMed ID: 34101071
    [Abstract] [Full Text] [Related]

  • 11. Integrating Semi-supervised and Supervised Learning Methods for Label Fusion in Multi-Atlas Based Image Segmentation.
    Zheng Q, Wu Y, Fan Y.
    Front Neuroinform; 2018 Dec 13; 12():69. PubMed ID: 30364123
    [Abstract] [Full Text] [Related]

  • 12. Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates.
    Pipitone J, Park MT, Winterburn J, Lett TA, Lerch JP, Pruessner JC, Lepage M, Voineskos AN, Chakravarty MM, Alzheimer's Disease Neuroimaging Initiative.
    Neuroimage; 2014 Nov 01; 101():494-512. PubMed ID: 24784800
    [Abstract] [Full Text] [Related]

  • 13. Entropy and distance maps-guided segmentation of articular cartilage: data from the Osteoarthritis Initiative.
    Li Z, Chen K, Liu P, Chen X, Zheng G.
    Int J Comput Assist Radiol Surg; 2022 Mar 01; 17(3):553-560. PubMed ID: 34988758
    [Abstract] [Full Text] [Related]

  • 14. Automatic atlas-based three-label cartilage segmentation from MR knee images.
    Shan L, Zach C, Charles C, Niethammer M.
    Med Image Anal; 2014 Oct 01; 18(7):1233-46. PubMed ID: 25128683
    [Abstract] [Full Text] [Related]

  • 15. Fully automated, level set-based segmentation for knee MRIs using an adaptive force function and template: data from the osteoarthritis initiative.
    Ahn C, Bui TD, Lee YW, Shin J, Park H.
    Biomed Eng Online; 2016 Aug 24; 15(1):99. PubMed ID: 27558127
    [Abstract] [Full Text] [Related]

  • 16. MTL-ABS3Net: Atlas-Based Semi-Supervised Organ Segmentation Network With Multi-Task Learning for Medical Images.
    Huang H, Chen Q, Lin L, Cai M, Zhang Q, Iwamoto Y, Han X, Furukawa A, Kanasaki S, Chen YW, Tong R, Hu H.
    IEEE J Biomed Health Inform; 2022 Aug 24; 26(8):3988-3998. PubMed ID: 35213319
    [Abstract] [Full Text] [Related]

  • 17. LOGISMOS--layered optimal graph image segmentation of multiple objects and surfaces: cartilage segmentation in the knee joint.
    Yin Y, Zhang X, Williams R, Wu X, Anderson DD, Sonka M.
    IEEE Trans Med Imaging; 2010 Dec 24; 29(12):2023-37. PubMed ID: 20643602
    [Abstract] [Full Text] [Related]

  • 18. Fully automated segmentation of cartilage from the MR images of knee using a multi-atlas and local structural analysis method.
    Lee JG, Gumus S, Moon CH, Kwoh CK, Bae KT.
    Med Phys; 2014 Sep 24; 41(9):092303. PubMed ID: 25186408
    [Abstract] [Full Text] [Related]

  • 19. Efficient Combination of CNN and Transformer for Dual-Teacher Uncertainty-guided Semi-supervised Medical Image Segmentation.
    Xiao Z, Su Y, Deng Z, Zhang W.
    Comput Methods Programs Biomed; 2022 Nov 24; 226():107099. PubMed ID: 36116398
    [Abstract] [Full Text] [Related]

  • 20. Semi Supervised Learning with Deep Embedded Clustering for Image Classification and Segmentation.
    Enguehard J, O'Halloran P, Gholipour A.
    IEEE Access; 2019 Nov 24; 7():11093-11104. PubMed ID: 31588387
    [Abstract] [Full Text] [Related]

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