Joint Scene and Object Tracking for Cost-Effective Augmented Reality Assisted Patient Positioning in Radiation Therapy
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Background and Objective: The research done in the field of Augmented Reality (AR) for patient positioning in radiation therapy is scarce. We propose an efficient and cost-effective algorithm for tracking the scene and the patient to interactively assist the patient's positioning process by providing visual feedback to the operator. Methods: We have taken advantage of the marker mapper algorithm combined with other steps including generalized ICP to track the patient. We track the environment using the UcoSLAM algorithm. The alignment between the 3D reference model and body marker map is calculated employing our efficient body reconstruction algorithm. Results: Our quantitative evaluation shows that we were able to achieve an average rotational error of 1.77 deg and a translational error of 7.28 mm. Our algorithm performed with an average frame rate of 19 fps. Furthermore, the qualitative results demonstrate the usefulness of our algorithm in patient positioning on different human subjects. Conclusion: Since our algorithm achieves a relatively high frame rate and accuracy without the usage of a dedicated GPU employing a regular laptop, it is a very cost-effective AR-based patient positioning method.
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