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Echocardiography is widely used in cardiac imaging for real-time, non-invasive assessment of heart anatomy and function. However, image interpretation can be challenging due to inherent noise, particularly speckle. This study compares artificial intelligence (AI) and human experts in interpreting parasternal long-axis (PLAX) echocardiographic images under increasing noise levels. While both AI and human performance declined with image quality, AI consistently outperformed humans, indicating its potential to enhance clinical decision-making in challenging imaging scenarios.

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Robustness of Human vs. AI Measurements Under Progressive Image Degradation

  • 会议论文

  • 发表日期：

    2026年

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  • Jevgeni Jevsikov,
  • Catherine C. Stowell,
  • Tiffany Ng,
  • Beth Unsworth,
  • Massoud Zolgharni,
  • Darrel P. Francis,
  • Charlotte H. Manisty,
  • Matthew J. Shun-Shin

摘要

Echocardiography is widely used in cardiac imaging for real-time, non-invasive assessment of heart anatomy and function. However, image interpretation can be challenging due to inherent noise, particularly speckle. This study compares artificial intelligence (AI) and human experts in interpreting parasternal long-axis (PLAX) echocardiographic images under increasing noise levels. While both AI and human performance declined with image quality, AI consistently outperformed humans, indicating its potential to enhance clinical decision-making in challenging imaging scenarios.