Javad Fotouhi1, Bernhard Fuerst1, Mathias Unberath1, Stefan Reichenstein1, Sing Chun Lee1, Alex A Johnson2, Greg M Osgood2, Mehran Armand3,4, Nassir Navab1,5. 1. Computer Aided Medical Procedures, Johns Hopkins University, Baltimore, MD, USA. 2. Department of Orthopaedic Surgery, Johns Hopkins Hospital, Baltimore, MD, USA. 3. Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA. 4. Applied Physics Laboratory, Johns Hopkins University, Laurel, MD, USA. 5. Computer Aided Medical Procedures, Technical University of Munich, Munich, Germany.
Abstract
PURPOSE: Cone-beam computed tomography (CBCT) is one of the primary imaging modalities in radiation therapy, dentistry, and orthopedic interventions. While CBCT provides crucial intraoperative information, it is bounded by a limited imaging volume, resulting in reduced effectiveness. This paper introduces an approach allowing real-time intraoperative stitching of overlapping and nonoverlapping CBCT volumes to enable 3D measurements on large anatomical structures. METHODS: A CBCT-capable mobile C-arm is augmented with a red-green-blue-depth (RGBD) camera. An offline cocalibration of the two imaging modalities results in coregistered video, infrared, and x-ray views of the surgical scene. Then, automatic stitching of multiple small, nonoverlapping CBCT volumes is possible by recovering the relative motion of the C-arm with respect to the patient based on the camera observations. We propose three methods to recover the relative pose: RGB-based tracking of visual markers that are placed near the surgical site, RGBD-based simultaneous localization and mapping (SLAM) of the surgical scene which incorporates both color and depth information for pose estimation, and surface tracking of the patient using only depth data provided by the RGBD sensor. RESULTS: On an animal cadaver, we show stitching errors as low as 0.33, 0.91, and 1.72 mm when the visual marker, RGBD SLAM, and surface data are used for tracking, respectively. CONCLUSIONS: The proposed method overcomes one of the major limitations of CBCT C-arm systems by integrating vision-based tracking and expanding the imaging volume without any intraoperative use of calibration grids or external tracking systems. We believe this solution to be most appropriate for 3D intraoperative verification of several orthopedic procedures.
PURPOSE: Cone-beam computed tomography (CBCT) is one of the primary imaging modalities in radiation therapy, dentistry, and orthopedic interventions. While CBCT provides crucial intraoperative information, it is bounded by a limited imaging volume, resulting in reduced effectiveness. This paper introduces an approach allowing real-time intraoperative stitching of overlapping and nonoverlapping CBCT volumes to enable 3D measurements on large anatomical structures. METHODS: A CBCT-capable mobile C-arm is augmented with a red-green-blue-depth (RGBD) camera. An offline cocalibration of the two imaging modalities results in coregistered video, infrared, and x-ray views of the surgical scene. Then, automatic stitching of multiple small, nonoverlapping CBCT volumes is possible by recovering the relative motion of the C-arm with respect to the patient based on the camera observations. We propose three methods to recover the relative pose: RGB-based tracking of visual markers that are placed near the surgical site, RGBD-based simultaneous localization and mapping (SLAM) of the surgical scene which incorporates both color and depth information for pose estimation, and surface tracking of the patient using only depth data provided by the RGBD sensor. RESULTS: On an animal cadaver, we show stitching errors as low as 0.33, 0.91, and 1.72 mm when the visual marker, RGBD SLAM, and surface data are used for tracking, respectively. CONCLUSIONS: The proposed method overcomes one of the major limitations of CBCT C-arm systems by integrating vision-based tracking and expanding the imaging volume without any intraoperative use of calibration grids or external tracking systems. We believe this solution to be most appropriate for 3D intraoperative verification of several orthopedic procedures.
Authors: S Schafer; S Nithiananthan; D J Mirota; A Uneri; J W Stayman; W Zbijewski; C Schmidgunst; G Kleinszig; A J Khanna; J H Siewerdsena Journal: Med Phys Date: 2011-08 Impact factor: 4.071
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: Daniel J Mirota; Ali Uneri; Sebastian Schafer; Sajendra Nithiananthan; Douglas D Reh; Masaru Ishii; Gary L Gallia; Russell H Taylor; Gregory D Hager; Jeffrey H Siewerdsen Journal: IEEE Trans Med Imaging Date: 2013-01-28 Impact factor: 10.048
Authors: Axel Sahovaler; Michael J Daly; Harley H L Chan; Prakash Nayak; Sharon Tzelnick; Michelle Arkhangorodsky; Jimmy Qiu; Robert Weersink; Jonathan C Irish; Peter Ferguson; Jay S Wunder Journal: JB JS Open Access Date: 2022-05-05