To enhance the interpretation of OCT volumetric data by integrating ex vivo middle ear models with in vivo OCT models, thereby improving diagnostic capabilities.
Key Findings:
C2P-Net successfully registers complete point cloud templates to partial point clouds of the middle ear, demonstrating robustness.
The Blender3D generation pipeline effectively simulates synthetic shape variants and noisy point clouds that closely resemble in vivo data.
Interpretation:
The proposed methods significantly enhance the accuracy of middle ear diagnostics by improving the interpretation quality of OCT data.
Limitations:
Absence of real OCT data with ground truth for effective training and validation.
Difficulty in establishing one-to-one correspondences due to noise and incompleteness in OCT models, which may hinder accuracy.
Conclusion:
The integration of ex vivo and in vivo models through advanced point cloud registration techniques shows great promise for enhancing middle ear diagnostics.
