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Research ArticleSpineE

Clinical Correlation of a New MR Imaging Method for Assessing Lumbar Foraminal Stenosis

H.-J. Park, S.S. Kim, S.-Y. Lee, N.-H. Park, M.-H. Rho, H.-P. Hong, H.-J. Kwag, S.-H. Kook and S.-H. Choi
American Journal of Neuroradiology May 2012, 33 (5) 818-822; DOI: https://doi.org/10.3174/ajnr.A2870
H.-J. Park
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S.-Y. Lee
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American Journal of Neuroradiology: 33 (5)
American Journal of Neuroradiology
Vol. 33, Issue 5
1 May 2012
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Cite this article
H.-J. Park, S.S. Kim, S.-Y. Lee, N.-H. Park, M.-H. Rho, H.-P. Hong, H.-J. Kwag, S.-H. Kook, S.-H. Choi
Clinical Correlation of a New MR Imaging Method for Assessing Lumbar Foraminal Stenosis
American Journal of Neuroradiology May 2012, 33 (5) 818-822; DOI: 10.3174/ajnr.A2870

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Clinical Correlation of a New MR Imaging Method for Assessing Lumbar Foraminal Stenosis
H.-J. Park, S.S. Kim, S.-Y. Lee, N.-H. Park, M.-H. Rho, H.-P. Hong, H.-J. Kwag, S.-H. Kook, S.-H. Choi
American Journal of Neuroradiology May 2012, 33 (5) 818-822; DOI: 10.3174/ajnr.A2870
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  • Lumbar Spinal Stenosis: How Is It Classified?
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    Journal of Orthopaedic Science 2023 28 1
  • Automated Pathogenesis-Based Diagnosis of Lumbar Neural Foraminal Stenosis via Deep Multiscale Multitask Learning
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    Neuroinformatics 2018 16 3-4
  • Diagnostic accuracy of contemporary multidetector computed tomography (MDCT) for the detection of lumbar disc herniation
    S. Notohamiprodjo, R. Stahl, M. Braunagel, P. M. Kazmierczak, K. M. Thierfelder, K. M. Treitl, S. Wirth, M. Notohamiprodjo
    European Radiology 2017 27 8
  • The Clinical Correlation of a New Practical MRI Method for Grading Cervical Neural Foraminal Stenosis Based on Oblique Sagittal Images
    Hee Jin Park, Sam Soo Kim, Chul Hee Han, So Yeon Lee, Eun Chul Chung, Mi Sung Kim, Heon Ju Kwon
    American Journal of Roentgenology 2014 203 2
  • Deep learning for automated, interpretable classification of lumbar spinal stenosis and facet arthropathy from axial MRI
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    European Radiology 2023 33 5

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