Robust methods for automatic image-to-world registration in cone-beam CT interventional guidance

被引:27
作者
Dang, H. [1 ]
Otake, Y. [1 ]
Schafer, S. [1 ]
Stayman, J. W. [1 ]
Kleinszig, G. [2 ]
Siewerdsen, J. H. [1 ]
机构
[1] Johns Hopkins Univ, Dept Biomed Engn, Baltimore, MD 21202 USA
[2] Siemens Healthcare XP Div, D-91052 Erlangen, Germany
基金
美国国家卫生研究院;
关键词
surgical navigation; surgical tracking; image-to-world registration; target registration error; registration accuracy; cone-beam CT; FLAT-PANEL DETECTOR; GUIDED SURGERY; CLINICAL-APPLICATIONS; FIDUCIAL MARKERS; ARM; MOBILE; PROJECTIONS; TRACKING; SEGMENTATION; ALGORITHM;
D O I
10.1118/1.4754589
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: Real-time surgical navigation relies on accurate image-to-world registration to align the coordinate systems of the image and patient. Conventional manual registration can present a workflow bottleneck and is prone to manual error and intraoperator variability. This work reports alternative means of automatic image-to-world registration, each method involving an automatic registration marker (ARM) used in conjunction with C-arm cone-beam CT (CBCT). The first involves a Known-Model registration method in which the ARM is a predefined tool, and the second is a Free-Form method in which the ARM is freely configurable. Methods: Studies were performed using a prototype C-arm for CBCT and a surgical tracking system. A simple ARM was designed with markers comprising a tungsten sphere within infrared reflectors to permit detection of markers in both x-ray projections and by an infrared tracker. The Known-Model method exercised a predefined specification of the ARM in combination with 3D-2D registration to estimate the transformation that yields the optimal match between forward projection of the ARM and the measured projection images. The Free-Form method localizes markers individually in projection data by a robust Hough transform approach extended from previous work, backprojected to 3D image coordinates based on C-arm geometric calibration. Image-domain point sets were transformed to world coordinates by rigid-body point-based registration. The robustness and registration accuracy of each method was tested in comparison to manual registration across a range of body sites (head, thorax, and abdomen) of interest in CBCT-guided surgery, including cases with interventional tools in the radiographic scene. Results: The automatic methods exhibited similar target registration error (TRE) and were comparable or superior to manual registration for placement of the ARM within similar to 200 mm of C-arm isocenter. Marker localization in projection data was robust across all anatomical sites, including challenging scenarios involving the presence of interventional tools. The reprojection error of marker localization was independent of the distance of the ARM from isocenter, and the overall TRE was dominated by the configuration of individual fiducials and distance from the target as predicted by theory. The median TRE increased with greater ARM-to-isocenter distance (e.g., for the Free-Form method, TRE increasing from 0.78 mm to 2.04 mm at distances of similar to 75 mm and 370 mm, respectively). The median TRE within similar to 200 mm distance was consistently lower than that of the manual method (TRE = 0.82 mm). Registration performance was independent of anatomical site (head, thorax, and abdomen). The Free-Form method demonstrated a statistically significant improvement (p = 0.0044) in reproducibility compared to manual registration (0.22 mm versus 0.30 mm, respectively). Conclusions: Automatic image-to-world registration methods demonstrate the potential for improved accuracy, reproducibility, and workflow in CBCT-guided procedures. A Free-Form method was shown to exhibit robustness against anatomical site, with comparable or improved TRE compared to manual registration. It was also comparable or superior in performance to a Known-Model method in which the ARM configuration is specified as a predefined tool, thereby allowing configuration of fiducials on the fly or attachment to the patient. (c) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4754589]
引用
收藏
页码:6484 / 6498
页数:15
相关论文
共 52 条
  • [1] An algorithm to extract three-dimensional motion by marker tracking in the kV projections from an on-board imager: four-dimensional cone-beam CT and tumor tracking implications
    Ali, Imad
    Alsbou, Nesreen
    Herman, Terence
    Ahmad, Salahuddin
    [J]. JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2011, 12 (02): : 223 - 238
  • [2] [Anonymous], 2004, POL VICR US GUID
  • [3] [Anonymous], 2000, MEDICAL IMAGE COMPUT
  • [4] VISUALIZATION OF ANTERIOR SKULL BASE DEFECTS WITH INTRAOPERATIVE CONE-BEAM CT
    Bachar, Gideon
    Barker, Emma
    Chan, Harley
    Daly, Michael J.
    Nithiananthan, Sajendra
    Vescan, Al
    Irish, Jonathan C.
    Siewerdsen, Jeffrey H.
    [J]. HEAD AND NECK-JOURNAL FOR THE SCIENCES AND SPECIALTIES OF THE HEAD AND NECK, 2010, 32 (04): : 504 - 512
  • [5] Intraoperative use of cone-beam computed tomography in a cadaveric ossified cochlea model
    Barker, Emma
    Trimble, Keith
    Chan, Harley
    Ramsden, James
    Nithiananthan, Sajendra
    James, Adrian
    Bachar, Gideon
    Daly, Mike
    Irish, Jonathan
    Siewerdsen, Jeff
    [J]. OTOLARYNGOLOGY-HEAD AND NECK SURGERY, 2009, 140 (05) : 697 - 702
  • [6] A METHOD FOR REGISTRATION OF 3-D SHAPES
    BESL, PJ
    MCKAY, ND
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1992, 14 (02) : 239 - 256
  • [7] An innovative phantom for quantitative and qualitative investigation of advanced x-ray imaging technologies
    Chiarot, CB
    Siewerdsen, JH
    Haycocks, T
    Moseley, DJ
    Jaffray, DA
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 2005, 50 (21) : N287 - N297
  • [8] Image-Guided Interventions: Technology Review and Clinical Applications
    Cleary, Kevin
    Peters, Terry M.
    [J]. ANNUAL REVIEW OF BIOMEDICAL ENGINEERING, VOL 12, 2010, 12 : 119 - 142
  • [9] Deguet A., 2008, INSIGHT
  • [10] MODEL-BASED OBJECT POSE IN 25 LINES OF CODE
    DEMENTHON, DF
    DAVIS, LS
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 1995, 15 (1-2) : 123 - 141