Deep learning-based fully automated body composition analysis of thigh CT: comparison with DXA measurement.

Journal: European radiology
PMID: 35435440

Abstract

OBJECTIVES: To compare volumetric CT with DL-based fully automated segmentation and dual-energy X-ray absorptiometry (DXA) in the measurement of thigh tissue composition.

Authors

  • Hye Jin Yoo
    Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
  • Young Jae Kim
    Department of Biomedical Engineering, College of Medicine, Gachon University, Gyeonggi-do, Republic of Korea.
  • Hyunsook Hong
    Medical Research Collaborating Center, Seoul National University Hospital, Seoul, South Korea.
  • Sung Hwan Hong
    Department of Radiology, Seoul National University College of Medicine, Seoul, Korea. drhong@snu.ac.kr.
  • Hee Dong Chae
    Department of Radiology, Seoul National University Hospital, Seoul, South Korea.
  • Ja-Young Choi
    Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.

Keywords

External Resources

Popular Topics
Recent Journals