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Automatic Registration Intra Oral Scan
Key Investigators
- Nathan Hutin (University of Michigan)
- Luc Anchling (University of Michigan, France)
- Lucia Cevidanes (University of Michigan, USA)
- Selene Barone (University of Catanzaro, Italy)
- Juan Prieto (University of North Carolina, USA)
- Jonas Bianchi (University of Pacifique, USA)
- Marcela Gurgel (University of Michigan, USA)
- Najla Al Turkestani (University of Michigan, USA)
- Felicia Miranda (University of Sao Paulo, Brezil)
- Denise Curado (University of Michigan, USA)
- Kinjal Mavani (University of Michigan, USA)
- Kinjal Mavani (University of Michigan, USA)
- Margaret Eason (University of Michigan, USA)
- Aron Aliage del Castilo (University of Michigan, USA)
Presenter location: In-person
Project Description
This project propose a tool to automatically register intra oral scan of upper jaw. The method can register growth and non-growing patient.
The registration method is based on neural network to create a region of interest on the palate, and ICP (Iterest Closest Point) to register.
The neural network has been trained with extraction and non-extraction case, growing and non-growing patient to have robust neural network.
We will leave the option to the users to also register the mandible by applying the transformation matrix of the maxilla to the mandible.
The actual code is on this repository.
Objective
- Start to implement automatic registration of IOS in Slicer
- Deploy Areg
Approach And Plan
- Find a method to perform Automatic Registration of IOS
- Train a neural network to create a region of interest
- Implement automatic registration for region of interest
Progress and Next Steps
Progress
- Method and script working
- User Interface
Next Steps
- Implement the method in Areg
- Deploy Areg in SlicerAutomatedDentalTools to be available to all users
Illustrations
Region of interest make by neural network
Legend :
- pink : initial scan
- blue : clinician registration
- yellow : automatic registration