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Automated Neonatal Hip Ultrasound System for Diagnosing Developmental Dysplasia of Hips Using Assistive AI.

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Title: Automated Neonatal Hip Ultrasound System for Diagnosing Developmental Dysplasia of Hips Using Assistive AI.
Authors: Lee, Young Seop1 (AUTHOR) liive2925@gmail.com, Kim, Young Jae1 (AUTHOR), Ryu, Jeong Won2 (AUTHOR), Lee, Su Yeol2 (AUTHOR), Kim, Kwang Gi1,3 (AUTHOR) kimkg@gachon.ac.kr
Source: Journal of Imaging Informatics in Medicine. Feb2026, Vol. 39 Issue 1, p518-531. 14p.
Subjects: Hip joint dislocation, Research funding, Data analysis, T-test (Statistics), Receiver operating characteristic curves, Artificial intelligence, Retrospective studies, Descriptive statistics, Dysplasia, Hip joint, Medical records, Acquisition of data, One-way analysis of variance, Statistics, Automation, Confidence intervals, Comparative studies, Sensitivity & specificity (Statistics), Algorithms, Inter-observer reliability, Children
Geographic Terms: South Korea
Abstract: This study aims to develop and evaluate an artificial intelligence (AI)-based diagnostic system for the diagnosis of developmental dysplasia of the hip (DDH) in infant hip ultrasonography. The Graf algorithm was employed to develop an automated model for diagnosing DDH, resulting in a DDH-assisted AI model with an average Graf angle error rate of 0.21 compared to expert diagnostics. NASNetMobile achieved the highest Area Under the Curve (AUC) of 0.864 (95% CI, 0.850–0.878), closely followed by MobileNetV1, DenseNet121, EfficientNetV2B0, NASNetMobile, and ResNet50. UnestedUNet demonstrated the highest overall performance, achieving Dice coefficients of 0.794 and a runtime of 40.078 ms, demonstrating its strong segmentation accuracy with moderate computational demands. DeepLabV3Plus, a handheld ultrasound device integrated with a smartphone, demonstrated a robust and efficient segmentation performance. This study highlights the transformative potential of integrating AI into portable ultrasound devices, enabling accurate, efficient, and accessible diagnostic solutions. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Imaging Informatics in Medicine is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
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DbLabel: Engineering Source
An: 191694173
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
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  Data: Automated Neonatal Hip Ultrasound System for Diagnosing Developmental Dysplasia of Hips Using Assistive AI.
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  Data: <searchLink fieldCode="AR" term="%22Lee%2C+Young+Seop%22">Lee, Young Seop</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> liive2925@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Kim%2C+Young+Jae%22">Kim, Young Jae</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ryu%2C+Jeong+Won%22">Ryu, Jeong Won</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lee%2C+Su+Yeol%22">Lee, Su Yeol</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kim%2C+Kwang+Gi%22">Kim, Kwang Gi</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<i> kimkg@gachon.ac.kr</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Imaging+Informatics+in+Medicine%22">Journal of Imaging Informatics in Medicine</searchLink>. Feb2026, Vol. 39 Issue 1, p518-531. 14p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Hip+joint+dislocation%22">Hip joint dislocation</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22T-test+%28Statistics%29%22">T-test (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Receiver+operating+characteristic+curves%22">Receiver operating characteristic curves</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Retrospective+studies%22">Retrospective studies</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Dysplasia%22">Dysplasia</searchLink><br /><searchLink fieldCode="DE" term="%22Hip+joint%22">Hip joint</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+records%22">Medical records</searchLink><br /><searchLink fieldCode="DE" term="%22Acquisition+of+data%22">Acquisition of data</searchLink><br /><searchLink fieldCode="DE" term="%22One-way+analysis+of+variance%22">One-way analysis of variance</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+studies%22">Comparative studies</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+%26+specificity+%28Statistics%29%22">Sensitivity & specificity (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Inter-observer+reliability%22">Inter-observer reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Children%22">Children</searchLink>
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  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22South+Korea%22">South Korea</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study aims to develop and evaluate an artificial intelligence (AI)-based diagnostic system for the diagnosis of developmental dysplasia of the hip (DDH) in infant hip ultrasonography. The Graf algorithm was employed to develop an automated model for diagnosing DDH, resulting in a DDH-assisted AI model with an average Graf angle error rate of 0.21 compared to expert diagnostics. NASNetMobile achieved the highest Area Under the Curve (AUC) of 0.864 (95% CI, 0.850–0.878), closely followed by MobileNetV1, DenseNet121, EfficientNetV2B0, NASNetMobile, and ResNet50. UnestedUNet demonstrated the highest overall performance, achieving Dice coefficients of 0.794 and a runtime of 40.078 ms, demonstrating its strong segmentation accuracy with moderate computational demands. DeepLabV3Plus, a handheld ultrasound device integrated with a smartphone, demonstrated a robust and efficient segmentation performance. This study highlights the transformative potential of integrating AI into portable ultrasound devices, enabling accurate, efficient, and accessible diagnostic solutions. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Imaging Informatics in Medicine is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=191694173
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1007/s10278-025-01498-3
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 518
    Subjects:
      – SubjectFull: Hip joint dislocation
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Data analysis
        Type: general
      – SubjectFull: T-test (Statistics)
        Type: general
      – SubjectFull: Receiver operating characteristic curves
        Type: general
      – SubjectFull: Artificial intelligence
        Type: general
      – SubjectFull: Retrospective studies
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Dysplasia
        Type: general
      – SubjectFull: Hip joint
        Type: general
      – SubjectFull: Medical records
        Type: general
      – SubjectFull: Acquisition of data
        Type: general
      – SubjectFull: One-way analysis of variance
        Type: general
      – SubjectFull: Statistics
        Type: general
      – SubjectFull: Automation
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      – SubjectFull: Confidence intervals
        Type: general
      – SubjectFull: Comparative studies
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      – SubjectFull: Sensitivity & specificity (Statistics)
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      – SubjectFull: Algorithms
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      – SubjectFull: Inter-observer reliability
        Type: general
      – SubjectFull: Children
        Type: general
      – SubjectFull: South Korea
        Type: general
    Titles:
      – TitleFull: Automated Neonatal Hip Ultrasound System for Diagnosing Developmental Dysplasia of Hips Using Assistive AI.
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            NameFull: Lee, Young Seop
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            – D: 01
              M: 02
              Text: Feb2026
              Type: published
              Y: 2026
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