ESTIMATING SHAPE CORRESPONDENCE FOR POPULATIONS OF OBJECTS WITH COMPLEX TOPOLOGY

Area of Science:

• Medical imaging analysis
• Geometric morphometrics
• Craniofacial surgery

Background:

• Statistical shape analysis (SSA) uses statistical methods to capture geometric properties from medical images.
• Orthognathic surgery corrects severe skeletal deformities of the mandible and maxilla.
• Existing SSA methods struggle with complex anatomical structures like the mandible due to topological limitations.

Purpose of the Study:

• To propose a novel methodology for statistical shape analysis of complex 3D geometries.
• To apply this methodology to analyze craniofacial structures in orthognathic surgery.
• To quantitatively assess bone healing and condylar remodeling post-surgery.

Main Methods:

• Development of a non-rigid deformation-based methodology for 3D geometries.
• Application to anatomical structures with thin and complex geometries.
• Quantitative characterization of bone healing and condylar remodeling.

Main Results:

• The proposed methodology accurately characterizes bone healing at the osteotomy site.
• Condylar remodeling was quantitatively assessed in three orthognathic surgery cases.
• Demonstrated effectiveness in analyzing complex craniofacial geometries.

Conclusions:

• Non-rigid deformation-based SSA is effective for analyzing complex anatomical structures.
• The methodology provides accurate quantitative insights into orthognathic surgery outcomes.
• This approach advances the geometric analysis of craniofacial bone dynamics.