Master thesis

Image based tracking for medical augmented reality in orthodontic application

Thesis by: Andre Aichert
External Supervision by: Wolfgang Wein
Supervision by: Tobias Reichl
Due date: October or November 2011

Abstract

This Master Thesis suggests a low-cost Augmented Reality system, termed OrthodontAR^?, for orthodontic applications and examines image-based tracking techniques specific to orthodontic use. The procedure addressed is guided bracket placement for orthodontic correction using dental braces. Related research has developed FEM simulations based on cone-beam CT reconstructions of teeth and bone. Such simulations could be used in the planning of optimal bracket placement and wire tension, such that patient teeth move in an optimal manner while minimizing rotation. The benefits would include reduced overall chair time due to fewer corrections and reduced likelihood of relapse due to reduced twisting. The system suggested in this thesis tackles the guided placement of brackets on the teeth, which is required to realize pre-procedure planning. Augmentation of a patient video with a newly placed bracket with its planned position would suffice. The surgeon could visually align planned and actual position in a video see-through head mounted display (HMD). To reduce technical complexity, the system shall be fully image guided. It shall rely on information from both CT and video images to track the patient's jaw. The goal of this thesis is to develop and evaluate image-based methods to overlay the CT of the patient with the video image. A prototype system shall be evaluated in terms of robustness and accuracy to determine if it meets practical requirements.

Methods

See above a photograph of a girl just before getting her dental braces and a volume rendering of the CT of her jaw on the right. The goal of this thesis is to evaluate the feasibility of a purely image guided system for orthodontic use. We suggest several methods to track an oral CT directly in a video image of a patient in order to guide the orthodontist during bracket placement.

The CT of an upper jaw registered to a frame from a patient video.

We suggest texturing an iso-surface to incorporate information from previous frames. In this image: a pig jaw textured from one video image and viewed at several angles.

We suggest using a dual-iso-surface rendering with surface normal distance based modulation. This type of rendering can be quite fast, but it shows the approximate gumline.

Slides

Kick-Off Slides

Final Presentation Slides