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<p>This article reviews advancements in fully automated abdominal CT interpretation over the past decade, with a focus on automated image analysis techniques such as quantitative analysis, computer-aided detection, and disease classification. For each abdominal organ, we review segmentation techniques, assess clinical applications and performance, and explore methods for detecting/classifying associated pathologies. We also highlight cutting-edge AI developments, including foundation models, large language models, and multimodal image analysis. While challenges remain in integrating AI into radiology practice, recent progress underscores its growing potential to streamline workflows, reduce radiologist burnout, and enhance patient care.</p>

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Progress in fully automated abdominal CT interpretation-an update over the past decade

  • 期刊论文

  • 发表日期：

    2025年7月8日

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  • Vivek Batheja,
  • Ronald Summers

摘要

This article reviews advancements in fully automated abdominal CT interpretation over the past decade, with a focus on automated image analysis techniques such as quantitative analysis, computer-aided detection, and disease classification. For each abdominal organ, we review segmentation techniques, assess clinical applications and performance, and explore methods for detecting/classifying associated pathologies. We also highlight cutting-edge AI developments, including foundation models, large language models, and multimodal image analysis. While challenges remain in integrating AI into radiology practice, recent progress underscores its growing potential to streamline workflows, reduce radiologist burnout, and enhance patient care.