3D Reconstruction Algorithm for Medical Image Skin Tissue Using Quadrilateral Mesh

This article presents a methodology for implementing 3D reconstruction of skin tissue from medical images using quadrilateral mesh structures. This algorithm proves particularly valuable in medical imaging applications and holds significant potential for clinical implementation. The quadrilateral mesh approach enables more precise reconstruction of skin tissue geometry from medical scan data, providing enhanced detail resolution and comprehensive volumetric analysis. From a technical perspective, the implementation typically involves mesh generation algorithms that convert 2D image slices into 3D surface models using quadrilateral elements, which offer better computational efficiency and smoother surface representation compared to triangular meshes for certain anatomical structures.

The methodological workflow generally includes image preprocessing, edge detection for boundary extraction, followed by quadrilateral mesh generation through algorithms like advancing front method or grid-based approaches. Key functions in the implementation often involve coordinate mapping between 2D pixels and 3D vertices, normal vector calculation for surface rendering, and mesh optimization techniques to maintain topological consistency. This approach assists medical professionals and researchers in gaining improved understanding of patient conditions through accurate 3D visualizations, thereby providing more reliable foundations for diagnosis and treatment planning. In clinical applications, the algorithm can be integrated with visualization libraries such as VTK or ITK for interactive 3D model manipulation.

In summary, the quadrilateral mesh-based 3D reconstruction algorithm for medical image skin tissue represents a promising and practical technology with robust implementation frameworks available in modern medical imaging software platforms.