Correction of patient motion in cone-beam CT using 3D-2D registration

被引:26
|
作者
Ouadah, S. [1 ]
Jacobson, M. [1 ]
Stayman, J. W. [1 ]
Ehtiati, T. [2 ]
Weiss, C. [1 ]
Siewerdsen, J. H. [1 ]
机构
[1] Johns Hopkins Univ, Dept Biomed Engn, Baltimore, MD 21205 USA
[2] Siemens Med Solutions USA Inc, Imaging & Therapy Syst, Hoffman Estates, IL 60192 USA
来源
PHYSICS IN MEDICINE AND BIOLOGY | 2017年 / 62卷 / 23期
基金
美国国家卫生研究院;
关键词
3D-2D registration; C-arm; cone-beam CT; image-guided interventions; motion correction; image quality; motion artifact; IMAGE REGISTRATION; COMPENSATION; CALIBRATION; REDUCTION;
D O I
10.1088/1361-6560/aa9254
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Cone-beam CT (CBCT) is increasingly common in guidance of interventional procedures, but can be subject to artifacts arising from patient motion during fairly long (similar to 5-60 s) scan times. We present a fiducial-free method to mitigate motion artifacts using 3D-2D image registration that simultaneously corrects residual errors in the intrinsic and extrinsic parameters of geometric calibration. The 3D-2D registration process registers each projection to a prior 3D image by maximizing gradient orientation using the covariance matrix adaptationevolution strategy optimizer. The resulting rigid transforms are applied to the system projection matrices, and a 3D image is reconstructed via model-based iterative reconstruction. Phantom experiments were conducted using a Zeego robotic C-arm to image a head phantom undergoing 5-15 cm translations and 5-15 degrees rotations. To further test the algorithm, clinical images were acquired with a CBCT head scanner in which long scan times were susceptible to significant patient motion. CBCT images were reconstructed using a penalized likelihood objective function. For phantom studies the structural similarity (SSIM) between motion-free and motion-corrected images was > 0.995, with significant improvement (p < 0.001) compared to the SSIM values of uncorrected images. Additionally, motion-corrected images exhibited a point-spread function with full-width at half maximum comparable to that of the motion-free reference image. Qualitative comparison of the motion-corrupted and motion-corrected clinical images demonstrated a significant improvement in image quality after motion correction. This indicates that the 3D-2D registration method could provide a useful approach to motion artifact correction under assumptions of local rigidity, as in the head, pelvis, and extremities. The method is highly parallelizable, and the automatic correction of residual geometric calibration errors provides added benefit that could be valuable in routine use.
引用
收藏
页码:8813 / 8831
页数:19
相关论文
共 50 条
  • [31] Neural patient-specific 3D-2D registration in laparoscopic liver resection
    Mhiri, Islem
    Pizarro, Daniel
    Bartoli, Adrien
    [J]. INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2024,
  • [32] Three-Dimensional (3D) Scatter Correction for Cone-Beam CT Using a 3D Fully Convolutional Neural Network (FCN)
    Jiang, Y.
    Yang, P.
    Yang, C.
    Niu, T.
    [J]. MEDICAL PHYSICS, 2019, 46 (06) : E130 - E131
  • [33] 3D IN VIVO DOSIMETRY USING MEGAVOLTAGE CONE-BEAM CT AND EPID DOSIMETRY
    van Elmpt, Wouter
    Nusten, Sebastiaan
    Petit, Steven
    Munheer, Ben
    Lambin, Philippe
    Dekker, Andre
    [J]. INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2009, 73 (05): : 1580 - 1587
  • [34] 3D Lung Tumor Motion Tracking Using MV Cone-Beam CT Acquisition with Synchronized Respiratory Monitoring
    Christensen, J.
    Tai, A.
    Gore, E.
    Li, X.
    [J]. MEDICAL PHYSICS, 2008, 35 (06)
  • [35] A 3D metal artifact correction method in cone-beam CT bone imaging by using an implant image library
    Zhang, Yan
    Ning, Ruola
    Conover, David
    [J]. MEDICAL IMAGING 2008: PHYSICS OF MEDICAL IMAGING, PTS 1-3, 2008, 6913
  • [36] Motion Estimation Using Cone-Beam CT Projection Images
    Becker, N.
    Kay, I.
    [J]. MEDICAL PHYSICS, 2009, 36 (06)
  • [37] Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery
    Espinel, Yamid
    Calvet, Lilian
    Botros, Karim
    Buc, Emmanuel
    Tilmant, Christophe
    Bartoli, Adrien
    [J]. MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2021, PT IV, 2021, 12904 : 657 - 666
  • [38] Using multiple images and contours for deformable 3D-2D registration of a preoperative CT in laparoscopic liver surgery
    Espinel, Yamid
    Calvet, Lilian
    Botros, Karim
    Buc, Emmanuel
    Tilmant, Christophe
    Bartoli, Adrien
    [J]. INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2022, 17 (12) : 2211 - 2219
  • [39] 3D Analytic Cone-Beam Reconstruction for Multiaxial CT Acquisitions
    Yin, Zhye
    De Man, Bruno
    Pack, Jed
    [J]. INTERNATIONAL JOURNAL OF BIOMEDICAL IMAGING, 2009, 2009
  • [40] Assess Interfractional Tumor Motion in SBRT Lung Treatment Using 4D Cone-Beam CT
    Li, J.
    Yu, Y.
    Xiao, Y.
    [J]. MEDICAL PHYSICS, 2013, 40 (06)