3D Reconstruction and alignment by consumer RGB-D sensors and fiducial planar markers for patient positioning in radiation therapy. (October 2019)

• Record Type: Journal Article
• Authors: Sarmadi, Hamid; Muñoz-Salinas, Rafael; Álvaro Berbís, M.; Luna, Antonio; Medina-Carnicer, R.
• Is Part Of: Computer methods and programs in biomedicine. Volume 180(2019)
• Publication Date: 2019-10
• Subjects: Patient positioning -- 3D Reconstructions -- RGB-D sensors -- Fiducial markers -- Radiation therapy -- Surface Guided Radiation Therapy (SGRT); Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2019.105004
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Cheap patient positioning method based on inexpensive consumer level RGB-D sensors. 3D reconstruction approach fuses artificial and natural visual landmarks using a hand-held RGB-D sensor. Our System does not need recalibration. Fiducial landmarks used for patient pose estimation. Generation of a visual output to help in positioning the patient. 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 ∘ 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.