Input your selected CT images, and we will analyze the results from the most accurate model perspective, along with an analysis of the surgical risks.
Input your selected CT images, and we will analyze the results from the most accurate model perspective, along with an analysis of the surgical risks.
The system uses a deep learning model based on Ultralytics YOLO to analyze dental CT images.
It detects key anatomical structures and estimates sinus-related angles to help assess potential surgical risks.
The model was developed through extensive experimentation.
Dozens of hyperparameter configurations and data augmentation strategies were tested across hundreds of training runs to identify the most robust model.
The final model was selected based on its performance on independent validation and test datasets.
The evaluation results show a median absolute deviation (MAD) of 5.44°, indicating stable and accurate angle predictions.
Our system supports standard dental CT or CBCT images.
For the best results, images should clearly show the maxillary sinus region and surrounding teeth structures.
The analysis usually takes only a few seconds.
Once the CT image is uploaded, the system automatically detects anatomical structures, analyzes sinus-related angles, and identifies potential missing teeth.
Yes. Uploaded images are used only for analysis and are not permanently stored on the server.