Hallux valgus diagnosis on X-rays with skeleton-guided diffusion

Abstract Medical image synthesis plays a crucial role in providing anatomically accurate images for diagnosis and treatment. Hallux valgus (HV), which affects approximately 19% of the global population, often requires frequent weight-bearing X-rays for assessment, which can be costly and logistically challenging in resource-limited healthcare settings due to the scarcity of horizontal foot imaging systems. Existing X-ray models often struggle to balance image fidelity, skeletal consistency, and physical constraints, particularly in diffusion-based methods that lack skeletal guidance. We propose the skeletal-constrained conditional diffusion model (SCCDM) along with two evaluation metrics, keypoint confidence-completeness (KCC) and keypoint structural consistency (KSC), to assess the anatomical plausibility of generated X-rays based on keypoint confidence and structural consistency. SCCDM incorporates multi-scale feature extraction and attention mechanisms, improving the structural similarity index by 5.72% (0.794) and the peak signal-to-noise ratio by 18.34% (21.40 dB). When combined with KCC and KSC, this method achieves average scores of 0.85 and 0.84, respectively, facilitating the clinical assessment of HV deformity and enabling more accurate surgical intervention. The code is available at https://github.com/midisec/SCCDM.