ImplantFormer: Vision Transformer based Implant Position Regression Using Dental CBCT Data

by   Xinquan Yang, et al.

Implant prosthesis is the most optimum treatment of dentition defect or dentition loss, which usually involves a surgical guide design process to decide the position of implant. However, such design heavily relies on the subjective experiences of dentist. To relieve this problem, in this paper, a transformer based Implant Position Regression Network, ImplantFormer, is proposed to automatically predict the implant position based on the oral CBCT data. The 3D CBCT data is firstly transformed into a series of 2D transverse plane slice views. ImplantFormer is then proposed to predict the position of implant based on the 2D slices of crown images. Convolutional stem and decoder are designed to coarsely extract image feature before the operation of patch embedding and integrate multi-levels feature map for robust prediction. The predictions of our network at tooth crown area are finally projected back to the positions at tooth root. As both long-range relationship and local features are involved, our approach can better represent global information and achieves better location performance than the state-of-the-art detectors. Experimental results on a dataset of 128 patients, collected from Shenzhen University General Hospital, show that our ImplantFormer achieves superior performance than benchmarks.


page 2

page 3

page 4

page 5

page 7

page 8

page 10

page 11


Two-Stream Regression Network for Dental Implant Position Prediction

In implant prosthesis treatment, the design of surgical guide requires l...

TCSloT: Text Guided 3D Context and Slope Aware Triple Network for Dental Implant Position Prediction

In implant prosthesis treatment, the surgical guide of implant is used t...

Short Range Correlation Transformer for Occluded Person Re-Identification

Occluded person re-identification is one of the challenging areas of com...

Conformer-based End-to-end Speech Recognition With Rotary Position Embedding

Transformer-based end-to-end speech recognition models have received con...

TCEIP: Text Condition Embedded Regression Network for Dental Implant Position Prediction

When deep neural network has been proposed to assist the dentist in desi...

DeepMatcher: A Deep Transformer-based Network for Robust and Accurate Local Feature Matching

Local feature matching between images remains a challenging task, especi...

Please sign up or login with your details

Forgot password? Click here to reset