Can real-time RGBD enhance intraoperative Cone-Beam CT?

Abstract

Cone-Beam Computed Tomography (CBCT) is an important 3D imaging technology for orthopedic, trauma, radiotherapy guidance, angiography, and dental applications. The major limitation of CBCT is the poor image quality due to scattered radiation, truncation, and patient movement. In this work, we propose to incorporate information from a co-registered Red-Green-Blue-Depth (RGBD) sensor attached near the detector plane of the C-arm to improve the reconstruction quality, as well as correcting for undesired rigid patient movement. Calibration of the RGBD and C-arm imaging devices is performed in two steps: (i) calibration of the RGBD sensor and the X-ray source using a multimodal checkerboard pattern, and (ii) calibration of the RGBD surface reconstruction to the CBCT volume. The patient surface is acquired during the CBCT scan and then used as prior information for the reconstruction using Maximum-Likelihood Expectation-Maximization. An RGBD-based simultaneous localization and mapping method is utilized to estimate the rigid patient movement during scanning. Performance is quantified and demonstrated using artificial data and bone phantoms with and without metal implants. Finally, we present movement-corrected CBCT reconstructions based on RGBD data on an animal specimen, where the average voxel intensity difference reduces from 0.157 without correction to 0.022 with correction. This work investigated the advantages of a C-arm X-ray imaging system used with an attached RGBD sensor. The experiments show the benefits of the opto/X-ray imaging system in: (i) improving the quality of reconstruction by incorporating the surface information of the patient, reducing the streak artifacts as well as the number of required projections, and (ii) recovering the scanning trajectory for the reconstruction in the presence of undesired patient rigid movement.