THA-Flow Generative Model: Prosthesis Geometry Prediction from Preoperative CT
Preoperative planning for total hip arthroplasty (THA) is commonly framed as selecting a single prosthesis configuration and placement for a patient's osseous anatomy. In practice, however, the same anatomy may admit several clinically reasonable solutions, making planning inherently a one-to-many problem that is better represented by a conditional probability distribution. We present THA-Flow, a conditional flow-matching model that generates three-dimensional prosthesis geometry directly from preoperative CT. Separate AutoencoderKL models compress preoperative bone anatomy and prosthesis geometry, while a three-dimensional UNet learns a rectified flow from Gaussian noise to the prosthesi...
| Authors | Yiping Wang, Jie Li, Jingyu Shen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 26 August 2026 |
| Last updated at source | 26 August 2026 |
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.