Intergrated Segmentation and Detection Models for Dentex Challenge 2023
This work addresses a domain-specific problem for dental diagnostics, aiming to improve efficiency for dentists, but it appears incremental as it builds on existing deep learning techniques without claiming major breakthroughs.
The authors tackled the problem of automatically detecting abnormal teeth and their enumeration IDs from dental panoramic X-rays for the Dentex Challenge 2023, proposing an integrated segmentation and detection method, but no concrete results or numbers are provided in the abstract.
Dental panoramic x-rays are commonly used in dental diagnosing. With the development of deep learning, auto detection of diseases from dental panoramic x-rays can help dentists to diagnose diseases more efficiently.The Dentex Challenge 2023 is a competition for automatic detection of abnormal teeth along with their enumeration ids from dental panoramic x-rays. In this paper, we propose a method integrating segmentation and detection models to detect abnormal teeth as well as obtain their enumeration ids.Our codes are available at https://github.com/xyzlancehe/DentexSegAndDet.