Head CBCT Tooth segmentation, STS3D2023 DataSet,Deep Learnning
- I have been engaged in CBCT segmentation based on deep learning for nearly ten years.
- The STS3D2023 dataset has been annotated at the instance level for each tooth in all data (approximately 500 CBCTs).
- We have trained CBCT on teeth, mandible, and neural tubes using the most advanced deep learning methods currently available, and can be said to have achieved the best results on the market.
- At present, the training model has over 2000 CBCT data and supports CBCT tooth segmentation collected by almost all devices on the market. It has high accuracy, full segmentation, and good edge effects.
- Friends who need labels for all STS3D2023 DataSets can contact me, but it's not free(Only limited to the labels of the data, the data is irrelevant to me).
- If you need to annotate a large amount of your own data, you can also contact me, but it is not free.
- After observing the visualization effects extensively, I have found that automatic model annotation is far better than manual annotation, and manual annotation is basically unable to achieve smoothness and edge accuracy. If needed, just leave your email and I will proactively contact you.