Progress in fully automated abdominal CT interpretation-an update over the past decade
Vivek Batheja1, Ronald Summers2
1National Institutes of Health, Bethesda, USA. bathejavivek@gwu.edu.
Abdominal Radiology (New York)
|July 8, 2025
Summary
This review covers a decade of progress in automated abdominal CT interpretation, highlighting AI techniques for image analysis, disease detection, and classification to improve radiology workflows and patient care.
Area of Science:
- Radiology
- Artificial Intelligence
- Medical Imaging
Background:
- Fully automated abdominal CT interpretation has seen significant advancements.
- AI-driven image analysis is transforming diagnostic capabilities.
Purpose of the Study:
- To review progress in automated abdominal CT interpretation over the last decade.
- To focus on AI techniques for quantitative analysis, detection, and classification of abdominal pathologies.
Main Methods:
- Review of segmentation techniques for abdominal organs.
- Assessment of clinical applications and performance of automated analysis.
- Exploration of AI developments like foundation models and multimodal analysis.
Main Results:
- Significant progress in automated image analysis for abdominal CT.
- Demonstrated potential of AI in detecting and classifying pathologies.
- Emerging AI technologies show promise for enhanced interpretation.
Conclusions:
- AI holds substantial potential to streamline radiology workflows.
- Automated interpretation can help reduce radiologist burnout.
- Advancements in AI are poised to enhance patient care in abdominal imaging.
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