Landmark localization and registration of 3D facial scans

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Landmark localization and registration of 3D facial scans

  1. 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. 2. What is the problem? <ul><li>To quantify 3D facial asymmetry </li></ul><ul><ul><li>Clinical diagnosis </li></ul></ul><ul><ul><li>Treatment planning </li></ul></ul><ul><ul><li>Post-treatment monitoring </li></ul></ul><ul><ul><li>Statistical studies on a large population </li></ul></ul>
  3. 3. <ul><li>What is rigid registration? </li></ul><ul><ul><li>Alignment of 2 or more faces </li></ul></ul><ul><li>Classical approach: Iterative Closest Point (ICP) algorithm </li></ul><ul><ul><li>Advantage </li></ul></ul><ul><ul><ul><li>no prior info needed </li></ul></ul></ul><ul><ul><li>Disadvantage </li></ul></ul><ul><ul><ul><li>random points used for matching  can lead to erroneous results </li></ul></ul></ul>Approach: rigid registration
  4. 4. Example
  5. 5. Our approach <ul><li>Rigid registration based on landmarks </li></ul><ul><li>Landmark detection via Statistical Shape Analysis </li></ul>
  6. 6. BtG project: Achievement 1 <ul><li>Improved accuracy </li></ul><ul><ul><li>Red – before BtG </li></ul></ul><ul><ul><li>Green – after BtG </li></ul></ul>
  7. 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. 8. 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 Test scan Reference scan
  9. 9. 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 Test scan Reference scan
  10. 10. 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 Test scan Reference scan Key Landmarks Coarse registration
  11. 11. 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 Test scan Reference scan
  12. 12. 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 Test scan Reference scan Fine registration
  13. 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. 14. Example ICP Proposed approach
  15. 15. BtG project: Achievement 2 <ul><li>User friendly GUI </li></ul><ul><ul><li>To ease burden on clinicians </li></ul></ul><ul><ul><li>User-feedback mechanisms </li></ul></ul>
  16. 16. Conclusions <ul><li>Achievements </li></ul><ul><ul><li>Improved landmark localisation accuracy </li></ul></ul><ul><ul><li>More user-friendly GUI with the user feedback </li></ul></ul><ul><li>Current work </li></ul><ul><ul><li>Clinical evaluation of the landmark detection accuracy </li></ul></ul><ul><ul><li>Validation of 3D facial scan registration accuracy </li></ul></ul><ul><ul><li>Further improving the GUI based on clinician feedback </li></ul></ul>Contact: [email_address] [email_address]

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