1. Landmark localization and registration of 3D facial scans for the evaluation of orthodontic treatments in maxillofacial and oral surgery
School of EECS: Prathap Nair, Dr Andrea Cavallaro
School of Medicine and Dentistry: Dr Lifong Zou
Mid-project update

2. What is the problem? To quantify 3D facial asymmetry
Clinical diagnosis
Treatment planning
Post-treatment monitoring
Statistical studies on a large population

3. Approach: rigid registration
What is rigid registration?
Alignment of 2 or more faces
Classical approach: Iterative Closest Point (ICP) algorithm
Advantage
no prior info needed
Disadvantage
random points used for matching  can lead to erroneous results

4. Example

5. Our approach Rigid registration based on landmarks
Landmark detection via Statistical Shape Analysis

6. BtG project: Achievement 1
Improved accuracy
Red – before BtG
Green – after BtG

7. Approach: overview Detection of Test Scan Landmark Points
Coarse registration using Key landmarks
Fine registration using the Semantic Regions
Detection of
Stable regions
Distance
estimation
Detection of
Landmark Points
Reference scan

8. Approach: overview Detection of Test Scan Landmark Points
Coarse registration using Key landmarks
Fine registration using the Semantic Regions
Detection of
Stable regions
Distance
estimation
Detection of
Landmark Points
Reference scan
Test scan
Reference scan

9. Approach: overview Detection of Test Scan Landmark Points
Coarse registration using Key landmarks
Fine registration using the Semantic Regions
Detection of
Stable regions
Distance
estimation
Detection of
Landmark Points
Reference scan
Test scan
Reference scan

10. Approach: overview Detection of Test Scan Landmark Points
Coarse registration using Key landmarks
Fine registration using the Semantic Regions
Detection of
Stable regions
Distance
estimation
Detection of
Landmark Points
Reference scan
Coarse registration
Test scan
Reference scan
Key Landmarks

11. Approach: overview Detection of Test Scan Landmark Points
Coarse registration using Key landmarks
Fine registration using the Semantic Regions
Detection of
Stable regions
Distance
estimation
Detection of
Landmark Points
Reference scan
Test scan
Reference scan

12. Approach: overview Detection of Test Scan Landmark Points
Coarse registration using Key landmarks
Fine registration using the Semantic Regions
Detection of
Stable regions
Distance
estimation
Detection of
Landmark Points
Reference scan
Fine registration
Test scan
Reference scan

13. Approach: overview Detection of Test Scan Landmark Points
Coarse registration using Key landmarks
Fine registration using the Semantic Regions
Detection of
Stable regions
Distance
estimation
Detection of
Landmark Points
Reference scan

14. Example
ICP
Proposed approach

15. BtG project: Achievement 2
User friendly GUI
To ease burden on clinicians
User-feedback mechanisms

16. Conclusions Achievements Current work
Improved landmark localisation accuracy
More user-friendly GUI with the user feedback
Current work
Clinical evaluation of the landmark detection accuracy
Validation of 3D facial scan registration accuracy
Further improving the GUI based on clinician feedback
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