A benchmark for comparison of dental radiography analysis algorithms

TLDR

Dental radiography is essential for diagnosis, treatment, and surgery, and recent work has focused on developing computerized X‑ray analysis systems for clinical use. The study introduces a framework for objectively evaluating automatic dental radiography analysis algorithms, detailing datasets, methods, results, and guidelines for future benchmark use. The benchmark comprises a bitewing radiograph anatomy repository, a cephalometric radiograph abnormality classification repository, and a quantitative evaluation protocol for algorithm comparison. Seven cephalometric and two bitewing analysis algorithms were compared, revealing that automatic dental radiography analysis remains challenging, and the datasets and evaluation software are released to the community. The benchmark and evaluation software are available at http://www-o.ntust.edu.tw/~cweiwang/ISBI2015/.

Abstract

Dental radiography plays an important role in clinical diagnosis, treatment and surgery. In recent years, efforts have been made on developing computerized dental X-ray image analysis systems for clinical usages. A novel framework for objective evaluation of automatic dental radiography analysis algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2015 Bitewing Radiography Caries Detection Challenge and Cephalometric X-ray Image Analysis Challenge. In this article, we present the datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark. The main contributions of the challenge include the creation of the dental anatomy data repository of bitewing radiographs, the creation of the anatomical abnormality classification data repository of cephalometric radiographs, and the definition of objective quantitative evaluation for comparison and ranking of the algorithms. With this benchmark, seven automatic methods for analysing cephalometric X-ray image and two automatic methods for detecting bitewing radiography caries have been compared, and detailed quantitative evaluation results are presented in this paper. Based on the quantitative evaluation results, we believe automatic dental radiography analysis is still a challenging and unsolved problem. The datasets and the evaluation software will be made available to the research community, further encouraging future developments in this field. (http://www-o.ntust.edu.tw/~cweiwang/ISBI2015/)