Automated segmentation of whole-body CT images for body composition analysis in pediatric patients using a deep neural network.
Seul Bi LeeYeon Jin ChoSoon Ho YoonYun Young LeeSoo-Hyun KimSeunghyun LeeYoung Hun ChoiJung-Eun CheonPublished in: European radiology (2022)
• We utilized transfer learning with a pre-trained segmentation algorithm for adult to develop an algorithm for automated segmentation of pediatric whole-body CT. • This algorithm showed excellent performance and was not affected by sex, age, or body mass index, except for precision in body muscle.
Keyphrases
- deep learning
- body composition
- convolutional neural network
- neural network
- resistance training
- body mass index
- machine learning
- computed tomography
- image quality
- dual energy
- bone mineral density
- contrast enhanced
- positron emission tomography
- skeletal muscle
- magnetic resonance imaging
- weight gain
- young adults
- childhood cancer
- electron transfer