Deep learning-based fully automated body composition analysis of thigh CT: comparison with DXA measurement.
Hye Jin YooYoung Jae KimHyunsook HongSung Hwan HongHee Dong ChaeJa Young ChoiPublished in: European radiology (2022)
) were developed using DXA data (g), age, height (cm), and body weight (kg) and good model performance was proven in the validation study.
Keyphrases
- body composition
- body weight
- deep learning
- bone mineral density
- resistance training
- artificial intelligence
- machine learning
- dual energy
- convolutional neural network
- body mass index
- big data
- computed tomography
- electronic health record
- image quality
- contrast enhanced
- high throughput
- magnetic resonance imaging
- positron emission tomography
- soft tissue
- high intensity
- physical activity
- magnetic resonance
- clinical evaluation