  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.

Computer Vision and Pattern Recognition