A New Method in Facial Registration in Clinics Based on Structure Light Images

TL;DR

This paper introduces a novel facial registration method combining structure light images and CT scans, achieving high accuracy and efficiency for neurosurgical applications.

Contribution

The study presents a new registration approach using key point recognition and ICP, improving accuracy and speed over traditional methods.

Findings

RMSE as low as 0.995913 mm after registration

Faster registration process compared to traditional methods

Effective registration of facial depth and clinical images

Abstract

Background and Objective: In neurosurgery, fusing clinical images and depth images that can improve the information and details is beneficial to surgery. We found that the registration of face depth images was invalid frequently using existing methods. To abundant traditional image methods with depth information, a method in registering with depth images and traditional clinical images was investigated. Methods: We used the dlib library, a C++ library that could be used in face recognition, and recognized the key points on faces from the structure light camera and CT image. The two key point clouds were registered for coarse registration by the ICP method. Fine registration was finished after coarse registration by the ICP method. Results: RMSE after coarse and fine registration is as low as 0.995913 mm. Compared with traditional methods, it also takes less time. Conclusions: The new method successfully registered the facial depth image from structure light images and CT with a low error, and that would be promising and efficient in clinical application of neurosurgery.