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Deep learning-based landmark recognition and angle measurement of full-leg plain radiographs can be adopted to assess lower extremity alignment.

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Title: Deep learning-based landmark recognition and angle measurement of full-leg plain radiographs can be adopted to assess lower extremity alignment.
Authors: Jo, Changwung1 (AUTHOR), Hwang, Doohyun1,2 (AUTHOR), Ko, Sunho1,2 (AUTHOR), Yang, Myung Ho1,2 (AUTHOR), Lee, Myung Chul1,2 (AUTHOR), Han, Hyuk-Soo1,2 (AUTHOR), Ro, Du Hyun1,2,3 (AUTHOR) duhyunro@gmail.com
Source: Knee Surgery, Sports Traumatology, Arthroscopy. Apr2023, Vol. 31 Issue 4, p1388-1397.
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  Data: Deep learning-based landmark recognition and angle measurement of full-leg plain radiographs can be adopted to assess lower extremity alignment.
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  Data: <searchLink fieldCode="JN" term="%22Knee+Surgery%2C+Sports+Traumatology%2C+Arthroscopy%22">Knee Surgery, Sports Traumatology, Arthroscopy</searchLink>. Apr2023, Vol. 31 Issue 4, p1388-1397.
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s00167-022-07124-x
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      – Text: English
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        PageCount: 10
        StartPage: 1388
    Titles:
      – TitleFull: Deep learning-based landmark recognition and angle measurement of full-leg plain radiographs can be adopted to assess lower extremity alignment.
        Type: main
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            NameFull: Jo, Changwung
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            NameFull: Hwang, Doohyun
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            NameFull: Ko, Sunho
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            NameFull: Yang, Myung Ho
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            NameFull: Lee, Myung Chul
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            NameFull: Han, Hyuk-Soo
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            NameFull: Ro, Du Hyun
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          Dates:
            – D: 01
              M: 04
              Text: Apr2023
              Type: published
              Y: 2023
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              Value: 31
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              Value: 4
          Titles:
            – TitleFull: Knee Surgery, Sports Traumatology, Arthroscopy
              Type: main
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