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Pubmed for Handhelds

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Journal Abstract Search

507 related items for PubMed ID: 35051149

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  • 3. Three-Dimensional Lumbosacral Reconstruction by An Artificial Intelligence-Based Automated MR Image Segmentation for Selecting the Approach of Percutaneous Endoscopic Lumbar Discectomy.
    Zhu Z, Liu E, Su Z, Chen W, Liu Z, Chen T, Lu H, Zhou J, Li Q, Pang S.
    Pain Physician; 2024 Feb; 27(2):E245-E254. PubMed ID: 38324790
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  • 4. Deep learning-based lumbosacral reconstruction for difficulty prediction of percutaneous endoscopic transforaminal discectomy at L5/S1 level: A retrospective cohort study.
    Fan G, Liu H, Wang D, Feng C, Li Y, Yin B, Zhou Z, Gu X, Zhang H, Lu Y, He S.
    Int J Surg; 2020 Oct; 82():162-169. PubMed ID: 32882401
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  • 5. Three-dimensional reconstruction of Kambin's triangle based on automated magnetic resonance image segmentation.
    Su Z, Liu Z, Wang M, Li S, Lin L, Yuan Z, Pang S, Feng Q, Chen T, Lu H.
    J Orthop Res; 2022 Dec; 40(12):2914-2923. PubMed ID: 35233815
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  • 6. 3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.
    Li X, Dou Q, Chen H, Fu CW, Qi X, Belavý DL, Armbrecht G, Felsenberg D, Zheng G, Heng PA.
    Med Image Anal; 2018 Apr; 45():41-54. PubMed ID: 29414435
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  • 7. Deep Learning-Based Automatic Segmentation of Lumbosacral Nerves on CT for Spinal Intervention: A Translational Study.
    Fan G, Liu H, Wu Z, Li Y, Feng C, Wang D, Luo J, Wells WM, He S.
    AJNR Am J Neuroradiol; 2019 Jun; 40(6):1074-1081. PubMed ID: 31147353
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  • 11. In vivo dynamic changes of dimensions in the lumbar intervertebral foramen.
    Zhong W, Driscoll SJ, Tsai TY, Wang S, Mao H, Cha TD, Wood KB, Li G.
    Spine J; 2015 Jul 01; 15(7):1653-9. PubMed ID: 25797808
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  • 12. Deep Learning-Based Automated Magnetic Resonance Image Segmentation of the Lumbar Structure and Its Adjacent Structures at the L4/5 Level.
    Wang M, Su Z, Liu Z, Chen T, Cui Z, Li S, Pang S, Lu H.
    Bioengineering (Basel); 2023 Aug 15; 10(8):. PubMed ID: 37627848
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  • 13. Spine Explorer: a deep learning based fully automated program for efficient and reliable quantifications of the vertebrae and discs on sagittal lumbar spine MR images.
    Huang J, Shen H, Wu J, Hu X, Zhu Z, Lv X, Liu Y, Wang Y.
    Spine J; 2020 Apr 15; 20(4):590-599. PubMed ID: 31759132
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  • 14. Validity and reliability of computerized measurement of lumbar intervertebral disc height and volume from magnetic resonance images.
    Neubert A, Fripp J, Engstrom C, Gal Y, Crozier S, Kingsley MI.
    Spine J; 2014 Nov 01; 14(11):2773-81. PubMed ID: 24929060
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  • 15. Percent spinal canal compromise on MRI utilized for predicting the need for surgical treatment in single-level lumbar intervertebral disc herniation.
    Carlisle E, Luna M, Tsou PM, Wang JC.
    Spine J; 2005 Nov 01; 5(6):608-14. PubMed ID: 16291099
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  • 19. Is age more than manual material handling associated with lumbar vertebral body and disc changes? A cross-sectional multicentre MRI study.
    Violante FS, Zompatori M, Lovreglio P, Apostoli P, Marinelli F, Bonfiglioli R.
    BMJ Open; 2019 Sep 18; 9(9):e029657. PubMed ID: 31537567
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