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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:

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Presentation on theme: "Landmark localization and registration of 3D facial scans for the evaluation of orthodontic treatments in maxillofacial and oral surgery School of EECS:"— Presentation transcript:

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 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

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

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

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

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

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

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

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

14 ICP Proposed approach Example

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

16 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:


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