Summary of Semi-supervised Classification Of Dental Conditions in Panoramic Radiographs Using Large Language Model and Instance Segmentation: a Real-world Dataset Evaluation, by Bernardo Silva et al.
Semi-supervised classification of dental conditions in panoramic radiographs using large language model and instance segmentation: A real-world dataset evaluation
by Bernardo Silva, Jefferson Fontinele, Carolina Letícia Zilli Vieira, João Manuel R.S. Tavares, Patricia Ramos Cury, Luciano Oliveira
First submitted to arxiv on: 25 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A semi-supervised learning framework is proposed for classifying thirteen dental conditions on panoramic radiographs, leveraging large language models to annotate common conditions. The approach employs a masked autoencoder for pre-training and a Vision Transformer to utilize unlabeled data. Validation is done using two extensive datasets containing 8,795 panoramic radiographs and 8,029 paired reports and images. Results consistently meet or surpass baseline metrics for the Matthews correlation coefficient, demonstrating effectiveness comparable to that of a junior specialist. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps doctors analyze dental x-rays better by training computers to recognize different conditions without needing as many labeled examples. They use special tools like language models and autoencoders to teach the computer to identify things in the x-ray images. The results show that this new approach is just as good as a junior doctor at recognizing certain conditions, which could make it easier for doctors to diagnose dental problems. |
Keywords
» Artificial intelligence » Autoencoder » Semi supervised » Vision transformer
