3차원 얼굴 재구성을 이용한 안면 백반증 면적 측정 프레임워크

Abstract

Vitiligo is a chronic autoimmune skin disorder characterized by depigmented patches caused by the loss of melanocytes. While not life-threatening, facial lesions can severely impact patients’ psychological well-being. Con- ventional assessments rely on 2D images, which inherently fail to capture the true spatial distribution of lesions due to limitations in perspective, curvature distortion, and occlusion along the facial contours. This study presents a novel 3D-based framework for analyzing vitiligo lesion distribution on the face using multi-view images and a 3D Morphable Model (3DMM). Facial meshes are reconstructed from frontal, left, and right images, and vitiligo masks are aligned to the 3D surface using UV mapping. By projecting lesion information onto a fully reconstructed 3D facial surface, the framework overcomes the structural blind spots of 2D analysis—capturing curvature, depth, and areas along the sides of the face that are otherwise distorted or hidden from view. A comparative analysis of 2D and 3D methods using patient data revealed that the 3D approach consistently estimated larger lesion areas, particularly in regions where 2D projections underestimate due to view-dependent loss or distortion. This 3D framework significantly enhances the anatomical accuracy and reliability of vitiligo assessment, providing a powerful tool for clinical eval- uation, longitudinal tracking, and therapeutic outcome measurement