landmark localization and registration of 3d facial scans for the evaluation of orthodontic...
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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
What is the problem?
• To quantify 3D facial asymmetry
• Clinical diagnosis• Treatment planning• Post-treatment monitoring• Statistical studies on a large population
• 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
Approach: rigid registration
Example
Our approach
• Rigid registration based on landmarks • Landmark detection via Statistical Shape Analysis
BtG project: Achievement 1
• Improved accuracy
Red – before BtG
Green – after BtG
Approach: overview
Test Scan
Reference scan
Detection of
Landmark
Points
Detection of
Landmark
Points
Coarse registration using
Key landmark
s
Detection of Stable regions
Fine registrat
ion using the
Semantic
Regions
Distance
estimation
Test scan Reference scan
Approach: overview
Test Scan
Reference scan
Detection of
Landmark
Points
Detection of
Landmark
Points
Coarse registration using
Key landmark
s
Detection of Stable regions
Fine registrat
ion using the
Semantic
Regions
Distance
estimation
Test scan Reference scan
Approach: overview
Test Scan
Reference scan
Detection of
Landmark
Points
Detection of
Landmark
Points
Coarse registration using
Key landmark
s
Detection of Stable regions
Fine registrat
ion using the
Semantic
Regions
Distance
estimation
Test scan Reference scan
Approach: overview
Test Scan
Reference scan
Detection of
Landmark
Points
Detection of
Landmark
Points
Coarse registration using
Key landmark
s
Detection of Stable regions
Fine registrat
ion using the
Semantic
Regions
Distance
estimation
Key Landmar
ks
Coarse registration
Test scan Reference scan
Approach: overview
Test Scan
Reference scan
Detection of
Landmark
Points
Detection of
Landmark
Points
Coarse registration using
Key landmark
s
Detection of Stable regions
Fine registrat
ion using the
Semantic
Regions
Distance
estimation
Test scan Reference scan
Approach: overview
Test Scan
Reference scan
Detection of
Landmark
Points
Detection of
Landmark
Points
Coarse registration using
Key landmark
s
Detection of Stable regions
Fine registrat
ion using the
Semantic
Regions
Distance
estimation
Fine registration
Approach: overview
Test Scan
Reference scan
Detection of
Landmark
Points
Detection of
Landmark
Points
Coarse registration using
Key landmark
s
Detection of Stable regions
Fine registrat
ion using the
Semantic
Regions
Distance
estimation
ICP Proposed approach
Example
BtG project: Achievement 2
• User friendly GUI• To ease burden on clinicians• User-feedback mechanisms
Conclusions
• Achievements• 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
Contact: