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Related Experiment Video

Updated: Dec 13, 2025

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
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Two-Dimensional Image-Based Screening Tool for Infants with Positional Cranial Deformities: A Machine Learning

Cecilia A Callejas Pastor1, Il-Young Jung2, Shinhye Seo1

  • 1Department of Biomedical Engineering, Chungnam National University College of Medicine, Daejeon 35015, Korea.

Diagnostics (Basel, Switzerland)
|July 26, 2020
PubMed
Summary

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A new, affordable 2D imaging method accurately screens infant positional cranial deformities like brachycephaly and plagiocephaly. This technique aids clinical assessment and home monitoring, offering a convenient alternative to costly 3D scanning.

Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Pediatric Health

Background:

  • Positional cranial deformities (PCDs) are common infant skull shape abnormalities.
  • Current diagnosis relies on expensive 3D scanning, limiting accessibility.
  • A need exists for cost-effective and convenient screening tools.

Purpose of the Study:

  • To develop and validate an inexpensive, rapid screening method for classifying infant cranial deformities.
  • To utilize 2D vertex cranial images and machine learning for deformity assessment.
  • To estimate key indices like cranial ratio (CR) and cranial vault asymmetry index (CVAI).

Main Methods:

  • A novel software was developed for image processing and machine learning-based estimation.
  • The method uses single 2D vertex cranial images from 80 subjects (174 measurements).
Keywords:
brachycephalycephalic ratiocranial vault asymmetry indexmachine learningplagiocephalypositional cranial deformities

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  • Support vector regression was employed to compare estimated CR and CVAI with 3D scan reference data.

    • Main Results:

    • High correlation coefficients were achieved: 0.85 for CR and 0.89 for CVAI.
    • The model demonstrated 86.7% classification accuracy for both brachycephaly and plagiocephaly using unseen test data.
    • The screening method effectively determined severity levels of common PCDs.

    Conclusions:

    • The proposed 2D imaging method offers a viable, low-cost alternative for screening infant cranial deformities.
    • This tool can support clinical evaluations and empower parents in monitoring their child's condition at home.
    • The findings highlight the potential of AI in accessible pediatric diagnostic tools.