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Alveolar Bone Segmentation Methods in Assessing the Effectiveness of Periodontal Defect Regeneration Through Machine Learning of CBCT Data: A Systematic Review.

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Title: Alveolar Bone Segmentation Methods in Assessing the Effectiveness of Periodontal Defect Regeneration Through Machine Learning of CBCT Data: A Systematic Review.
Authors: Mohammed, Mahmud1,2 (AUTHOR) mahmud.mohammed@my.jcu.edu.au, Fernandez-Medina, Tulio1,3 (AUTHOR), Rajashekhar, Manjunath1 (AUTHOR), Baker, Stephanie4 (AUTHOR), Jennings, Ernest1 (AUTHOR), DeivanayagamPillai, Nagarajan (AUTHOR) nagarajand@care.edu.in
Source: International Journal of Biomedical Imaging. 12/21/2025, Vol. 2025, p1-15. 15p.
Database: Academic Search Ultimate
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  Data: Alveolar Bone Segmentation Methods in Assessing the Effectiveness of Periodontal Defect Regeneration Through Machine Learning of CBCT Data: A Systematic Review.
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1155/ijbi/9065572
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      – Code: eng
        Text: English
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        PageCount: 15
        StartPage: 1
    Titles:
      – TitleFull: Alveolar Bone Segmentation Methods in Assessing the Effectiveness of Periodontal Defect Regeneration Through Machine Learning of CBCT Data: A Systematic Review.
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          Name:
            NameFull: Mohammed, Mahmud
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            NameFull: Fernandez-Medina, Tulio
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            NameFull: Rajashekhar, Manjunath
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            NameFull: Baker, Stephanie
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            NameFull: Jennings, Ernest
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            NameFull: DeivanayagamPillai, Nagarajan
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            – D: 21
              M: 12
              Text: 12/21/2025
              Type: published
              Y: 2025
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              Value: 2025
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            – TitleFull: International Journal of Biomedical Imaging
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