3D cephalometric landmark detection by multiple stage deep reinforcement learning

Abstract The lengthy time needed for manual landmarking has delayed the widespread adoption of three-dimensional (3D) cephalometry. We here propose an automatic 3D cephalometric annotation system based on multi-stage deep reinforcement learning (DRL) and volume-rendered imaging. This system consider...

Full description

Bibliographic Details
Main Authors: Sung Ho Kang, Kiwan Jeon, Sang-Hoon Kang, Sang-Hwy Lee
Format: Article
Language:English
Published: Nature Publishing Group 2021-09-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-97116-7