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Robustness of Human vs. AI Measurements Under Progressive Image Degradation
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DOI：10.1007/978-3-032-00656-1_19.png)
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Abstract
En 中文
Echocardiography is widely used in cardiac imaging for realtime, 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.
Keywords:
Echocardiography
Computer Vision
Deep Learning
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