Skeleton-Guided Diffusion Model for Accurate Foot X-ray Synthesis in Hallux Valgus Diagnosis

TL;DR

This paper introduces a skeletal-guided diffusion model for synthesizing accurate foot X-ray images, enhancing image quality and skeletal consistency for better hallux valgus diagnosis.

Contribution

It proposes SCCDM, a novel diffusion model with skeletal guidance, and KCC, a foot evaluation method, improving image fidelity and clinical assessment accuracy.

Findings

SSIM improved by 5.72% to 0.794

PSNR increased by 18.34% to 21.40 dB

KCC score of 0.85 indicates strong clinical relevance

Abstract

Medical image synthesis plays a crucial role in providing anatomically accurate images for diagnosis and treatment. Hallux valgus, which affects approximately 19% of the global population, requires frequent weight-bearing X-rays for assessment, placing additional strain on both patients and healthcare providers. 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) and introduce KCC, a foot evaluation method utilizing skeletal landmarks. SCCDM incorporates multi-scale feature extraction and attention mechanisms, improving the Structural Similarity Index (SSIM) by 5.72% (0.794) and Peak Signal-to-Noise Ratio (PSNR) by 18.34% (21.40 dB). When combined with KCC, the model achieves an average score of 0.85, demonstrating strong clinical applicability. The code is available at https://github.com/midisec/SCCDM.