CGI-Automatic Malocclusion Treatment Planning 2024 (CGI-AMTP2024) Challenge

Challenge Introduction

Malocclusion refers to a misalignment or incorrect relationship between the teeth of upper and lower jaw arches when they approach each other as the jaws close. Correction of malocclusion is an orthodontic treatment to achieve optimum relations in physiologic and esthetic harmony among cranial structures and occlusion. The treatment involves adjusting facial bones and teeth by aligning and/or extracting teeth. Current manual or computer-aided treatment planning process is laborious and time-consuming as it requires several revisions from orthodontists. Therefore, an effective treatment planning system is essential to help orthodontists to analyze the malocclusion cases, streamline treatment workflow and enhance overall efficiency.

To promote the application of machine learning and deep learning algorithms in computer-aided automatic malocclusion treatment planning, we propose Automatic Malocclusion Treatment Planning (AMTP) Challenge.

Task: In this challenge, we provide a dataset that includes the point clouds of 32 teeth from a patient and corresponding transformation matrix of the teeth. Participants are required to train on this dataset, and predict the transformation matrix of the teeth after treatment. The performance will be evaluated by cosine similarity accuracy (CSA) and target registration error (TRE). The ranking is determined by prioritizing the larger TRE scores, with the smaller CSA scores used as a tie-breaker when necessary.

Challenge Organization

Challenge co-chairs

  • Lingyong Jiang, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
  • Bin Sheng, Shanghai Jiao Tong University, Shanghai, China
  • Jinman Kim, The University of Sydney, Sydney, Australia
  • Lei Bi, Shanghai Jiao Tong University, Shanghai, China

Organizing Team

  • Lei Bi, Shanghai Jiao Tong University, Shanghai, China
  • Xiaoshuang Li, Shanghai Jiao Tong University, Shanghai, China
  • Miri Chung, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
  • Anushka Kharbanda, The University of Sydney, Sydney, Australia
  • Lingyong Jiang, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
  • Bin Sheng, Shanghai Jiao Tong University, Shanghai, China
  • Jinman Kim, The University of Sydney, Sydney, Australia

Challenge Website

CGI-AMTP2024

Challenge Contact

For any questions, please contact the challenge chairs via E-mail: cgi_amtp2024@163.com.