Automated L3 slice selection and comprehensive body composition analysis using advanced deep learning technology
Clinical Trial Plan Approval
Artificial Intelligence Medical Devices
It is a medical image detection and diagnosis assistance software that automatically selects measurement indicators of abdominal CT images and automatically analyzes muscles and fat by developing and applying an L3 automatic selection algorithm using a deep learning model to help medical staff make diagnostic decisions about sarcopenia, sarcopenia, and obesity.
If you are using AID-U™ for research or publication, please include the following sentence in the Methods section of your paper:
Body composition for sarcopenia assessment was evaluated on CT using artificial intelligence software (AID-U™, iAID inc, Seoul, Korea), a fully automatic deep learning system for L3 selection and body composition analysis1
▷ Please copy and paste the sentence directly into your manuscript.
▷ If you have questions about how to cite our software, feel free to contact us.
Fully automated system for L3 slice detection and body composition analysis using state-of-the-art deep learning algorithms.
Comprehensive automated analysis with detailed reporting
Comprehensive PDF reports with automated L3 slice selection and body composition analysis
Export detailed measurement data in CSV format for statistical analysis
High-resolution segmented images showing muscle and fat distribution
Detailed measurements including skeletal muscle area, visceral fat area, and body composition indices