Abstract
A large number of people require surgical or orthodontic treatment to correct jaw deformities. The accuracy of surgical planning is essential to the success of craniomaxillofacial (CMF) surgery. An accurate surgical plan greatly relies on a patient-specific reference model. The current challenge is a lack of this reference model. As a result, the outcome of surgery is currently dependent on the surgeon's diagnoses and experience. This chapter introduces a method to automatically estimate an anatomically correct reference shape of the jaws for the patient requiring orthognathic surgery. The method is based on sparse shape composition and is data-driven. It can effectively estimate the normal shape of the maxilla and mandible.
Original language | English (US) |
---|---|
Title of host publication | Machine Learning in Dentistry |
Publisher | Springer International Publishing |
Pages | 105-114 |
Number of pages | 10 |
ISBN (Electronic) | 9783030718817 |
ISBN (Print) | 9783030718800 |
DOIs | |
State | Published - Jul 24 2021 |
Keywords
- Craniomaxillofacial deformities
- Shape composition
- Sparse representation
- Surgical planning
ASJC Scopus subject areas
- Dentistry(all)
- Computer Science(all)