Intergrated Segmentation and Detection Models for Dentex Challenge 2023

TL;DR

This paper presents an integrated segmentation and detection approach for automatically identifying and enumerating abnormal teeth in dental panoramic x-rays, aiming to assist dentists in diagnosis.

Contribution

It introduces a novel combined segmentation and detection model specifically designed for the Dentex Challenge 2023, improving automatic abnormal teeth detection.

Findings

Effective detection of abnormal teeth achieved

Codes are publicly available for reproducibility

Enhanced accuracy over baseline methods

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.