3D Reconstruction and Alignment by Consumer RGB-D Sensors and Fiducial Planar Markers for Patient Positioning in Radiation Therapy

TL;DR

This paper introduces a cost-effective, real-time 3D reconstruction method using consumer RGB-D sensors and fiducial markers for accurate patient positioning in radiation therapy, eliminating the need for expensive hardware.

Contribution

The novel approach combines real-time 3D reconstruction with artificial landmarks to automatically align patient scans without system calibration, suitable for clinical settings.

Findings

Median translational error of 1 cm

Median rotational error of 1 degree

Provides visual overlay and error maps for pose correction

Abstract

BACKGROUND AND OBJECTIVE: Patient positioning is a crucial step in radiation therapy, for which non-invasive methods have been developed based on surface reconstruction using optical 3D imaging. However, most solutions need expensive specialized hardware and a careful calibration procedure that must be repeated over time.This paper proposes a fast and cheap patient positioning method based on inexpensive consumer level RGB-D sensors. METHODS: The proposed method relies on a 3D reconstruction approach that fuses, in real-time, artificial and natural visual landmarks recorded from a hand-held RGB-D sensor. The video sequence is transformed into a set of keyframes with known poses, that are later refined to obtain a realistic 3D reconstruction of the patient. The use of artificial landmarks allows our method to automatically align the reconstruction to a reference one, without the need of calibrating the system with respect to the linear accelerator coordinate system. RESULTS:The experiments conducted show that our method obtains a median of 1 cm in translational error, and 1 degree of rotational error with respect to reference pose. Additionally, the proposed method shows as visual output overlayed poses (from the reference and the current scene) and an error map that can be used to correct the patient's current pose to match the reference pose. CONCLUSIONS: A novel approach to obtain 3D body reconstructions for patient positioning without requiring expensive hardware or dedicated graphic cards is proposed. The method can be used to align in real time the patient's current pose to a preview pose, which is a relevant step in radiation therapy.