Javad Fotouhi1, Bernhard Fuerst2, Wolfgang Wein3, Nassir Navab2,4. 1. Computer Aided Medical Procedures, Johns Hopkins University, Baltimore, MD, USA. fotouhi@jhu.edu. 2. Computer Aided Medical Procedures, Johns Hopkins University, Baltimore, MD, USA. 3. ImFusion GmbH, Munich, Germany. 4. Computer Aided Medical Procedures, Technische Universität München, Munich, Germany.
Abstract
PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.
PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.
Authors: Javad Fotouhi; Bernhard Fuerst; Alex Johnson; Sing Chun Lee; Russell Taylor; Greg Osgood; Nassir Navab; Mehran Armand Journal: Int J Comput Assist Radiol Surg Date: 2017-05-19 Impact factor: 2.924
Authors: Javad Fotouhi; Clayton P Alexander; Mathias Unberath; Giacomo Taylor; Sing Chun Lee; Bernhard Fuerst; Alex Johnson; Greg Osgood; Russell H Taylor; Harpal Khanuja; Mehran Armand; Nassir Navab Journal: J Med Imaging (Bellingham) Date: 2018-01-04
Authors: Sebastian Andress; Alex Johnson; Mathias Unberath; Alexander Felix Winkler; Kevin Yu; Javad Fotouhi; Simon Weidert; Greg Osgood; Nassir Navab Journal: J Med Imaging (Bellingham) Date: 2018-01-26
Authors: Javad Fotouhi; Bernhard Fuerst; Alex Johnson; Sing Chun Lee; Russell Taylor; Greg Osgood; Nassir Navab; Mehran Armand Journal: Int J Comput Assist Radiol Surg Date: 2017-05-19 Impact factor: 2.924
Authors: Javad Fotouhi; Bernhard Fuerst; Mathias Unberath; Stefan Reichenstein; Sing Chun Lee; Alex A Johnson; Greg M Osgood; Mehran Armand; Nassir Navab Journal: Med Phys Date: 2018-04-10 Impact factor: 4.071
Authors: Sing Chun Lee; Bernhard Fuerst; Keisuke Tateno; Alex Johnson; Javad Fotouhi; Greg Osgood; Federico Tombari; Nassir Navab Journal: Healthc Technol Lett Date: 2017-09-14