Fully Automatic Measurement of Hip Joint Anteversion Angle on CT Images Using Deep Learning
A fully automatic system is developed for hip joint segmentation and measurement of hip joint anteversion angle (AA) by combining a U-Net (including an encoder with a VGG-based transfer learning) with an angular regression. The integration of three-dimensional point cloud-based hip joint AA regression with the proposed U-Net model enables fully automatic measurement of the hip joint AA.
Authors
- Pei Yang
- Sen Luo
- Yongqiang Bai (ORCID: https://orcid.org/0000-0002-4432-6593)
- Shaojie Tang (ORCID: https://orcid.org/0000-0003-1323-6939)
Institutions
- Second Affiliated Hospital of Xi'an Jiaotong University (CN)
- Xi’an University of Posts and Telecommunications (CN)
Publication Details
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1109/icmee63700.2024.11025370
- Primary Topic
- Hip disorders and treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00