Skip to content

Solution to MICCAI 2024 Challenge 3DTeethLand

Notifications You must be signed in to change notification settings

bibi547/TL-DETR

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Tooth Landmark Detection

End-to-End 3D Tooth Landmark Detection

This work is the third solution of MICCAI 2024 Challenge 3DTeethLand.

It is also an extended application of KeypointDETR for tooth landmark detection.

Run

Data preprocessing

  1. First, individual teeth are cropped based on the segmentation ground truth provided by Teeth3DS. scripts/seg_to_single/segment_patch
  2. Assign ground truth landmarks to each tooth patch. scripts/seg_to_single/tooth_landmarks
  3. Generate the geodesic distance maps for all landmarks on each tooth patch. scripts/geodesic_distance

Train

python train.py

Test

python test.py

Inference

  1. First, the 3D tooth segmentation method is executed to crop tooth patches from the segmentation results.
  2. Run TL-DETR to detect landmarks on each tooth and map back to the original jaw models.

Cite

@inproceedings{jin2024keypointdetr,
  title={KeypointDETR: an end-to-end 3d keypoint detector},
  author={Jin, Hairong and Shen, Yuefan and Lou, Jianwen and Zhou, Kun and Zheng, Youyi},
  booktitle={ECCV},
  year={2024}
}

About

Solution to MICCAI 2024 Challenge 3DTeethLand

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages