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Journal Abstract Search

207 related items for PubMed ID: 34101071

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

  • 2. The optimisation of deep neural networks for segmenting multiple knee joint tissues from MRIs.
    Kessler DA, MacKay JW, Crowe VA, Henson FMD, Graves MJ, Gilbert FJ, Kaggie JD.
    Comput Med Imaging Graph; 2020 Dec; 86():101793. PubMed ID: 33075675
    [Abstract] [Full Text] [Related]

  • 3. Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the Osteoarthritis Initiative.
    Ambellan F, Tack A, Ehlke M, Zachow S.
    Med Image Anal; 2019 Feb; 52():109-118. PubMed ID: 30529224
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  • 4. 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; 17(3):553-560. PubMed ID: 34988758
    [Abstract] [Full Text] [Related]

  • 5. A Coarse-to-Fine Framework for Automated Knee Bone and Cartilage Segmentation Data from the Osteoarthritis Initiative.
    Deng Y, You L, Wang Y, Zhou X.
    J Digit Imaging; 2021 Aug; 34(4):833-840. PubMed ID: 34031789
    [Abstract] [Full Text] [Related]

  • 6. Automated cartilage and meniscus segmentation of knee MRI with conditional generative adversarial networks.
    Gaj S, Yang M, Nakamura K, Li X.
    Magn Reson Med; 2020 Jul; 84(1):437-449. PubMed ID: 31793071
    [Abstract] [Full Text] [Related]

  • 7. Use of 2D U-Net Convolutional Neural Networks for Automated Cartilage and Meniscus Segmentation of Knee MR Imaging Data to Determine Relaxometry and Morphometry.
    Norman B, Pedoia V, Majumdar S.
    Radiology; 2018 Jul; 288(1):177-185. PubMed ID: 29584598
    [Abstract] [Full Text] [Related]

  • 8. Simultaneous super-resolution and contrast synthesis of routine clinical magnetic resonance images of the knee for improving automatic segmentation of joint cartilage: data from the Osteoarthritis Initiative.
    Neubert A, Bourgeat P, Wood J, Engstrom C, Chandra SS, Crozier S, Fripp J.
    Med Phys; 2020 Oct; 47(10):4939-4948. PubMed ID: 32745260
    [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; 122():102213. PubMed ID: 34823835
    [Abstract] [Full Text] [Related]

  • 10. 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]

  • 11. Fully Automatic Knee Joint Segmentation and Quantitative Analysis for Osteoarthritis from Magnetic Resonance (MR) Images Using a Deep Learning Model.
    Tang X, Guo D, Liu A, Wu D, Liu J, Xu N, Qin Y.
    Med Sci Monit; 2022 Jun 14; 28():e936733. PubMed ID: 35698440
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  • 15. 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 14; 29(12):2023-37. PubMed ID: 20643602
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  • 16. Deep convolutional neural network for segmentation of knee joint anatomy.
    Zhou Z, Zhao G, Kijowski R, Liu F.
    Magn Reson Med; 2018 Dec 14; 80(6):2759-2770. PubMed ID: 29774599
    [Abstract] [Full Text] [Related]

  • 17. Automated anomaly-aware 3D segmentation of bones and cartilages in knee MR images from the Osteoarthritis Initiative.
    Woo B, Engstrom C, Baresic W, Fripp J, Crozier S, Chandra SS.
    Med Image Anal; 2024 Apr 14; 93():103089. PubMed ID: 38246088
    [Abstract] [Full Text] [Related]

  • 18. Automated MRI assessment confirms cartilage thickness modification in patients with knee osteoarthritis: post-hoc analysis from a phase II sprifermin study.
    Brett A, Bowes MA, Conaghan PG, Ladel C, Guehring H, Moreau F, Eckstein F.
    Osteoarthritis Cartilage; 2020 Nov 14; 28(11):1432-1436. PubMed ID: 32860991
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  • 20. Modified radial-search algorithm for segmentation of tibiofemoral cartilage in MR images of patients with subchondral lesion.
    Thaha R, Jogi SP, Rajan S, Mahajan V, Venugopal VK, Mehndiratta A, Singh A.
    Int J Comput Assist Radiol Surg; 2020 Mar 14; 15(3):403-413. PubMed ID: 31927688
    [Abstract] [Full Text] [Related]

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