Performance evaluation of MIND demons deformable registration of MR and CT images in spinal interventions

被引:7
|
作者
Reaungamornrat, S. [1 ]
De Silva, T. [2 ]
Uneri, A. [1 ]
Goerres, J. [2 ]
Jacobson, M. [2 ]
Ketcha, M. [2 ]
Vogt, S. [3 ]
Kleinszig, G. [3 ]
Khanna, A. J. [4 ]
Wolinsky, J-P [5 ]
Prince, J. L. [1 ,2 ,6 ]
Siewerdsen, J. H. [1 ,2 ,5 ]
机构
[1] Johns Hopkins Univ, Dept Comp Sci, Baltimore, MD 21218 USA
[2] Johns Hopkins Univ, Dept Biomed Engn, Baltimore, MD 21202 USA
[3] Siemens Healthcare XP Div, D-91052 Erlangen, Germany
[4] Johns Hopkins Orthopaed Surgery DC, Dept Orthopaed Surg, Bethesda, MD 20817 USA
[5] Johns Hopkins Univ Hosp, Dept Neurosurg, Baltimore, MD 21202 USA
[6] Johns Hopkins Univ, Dept Elect & Comp Engn, Baltimore, MD 21218 USA
基金
美国国家卫生研究院;
关键词
deformable image registration; Demons algorithm; symmetric diffeomorphism; multimodality image registration; MIND; CT; image-guided surgery; LUMBAR INTERBODY FUSION; COMPUTED-TOMOGRAPHY; PEDICLE SCREWS; CERVICAL-SPINE; SURGERY; NAVIGATION; PLACEMENT; TRAUMA; ARM; COMPLICATIONS;
D O I
10.1088/0031-9155/61/23/8276
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Accurate intraoperative localization of target anatomy and adjacent nervous and vascular tissue is essential to safe, effective surgery, and multimodality deformable registration can be used to identify such anatomy by fusing preoperative CT or MR images with intraoperative images. A deformable image registration method has been developed to estimate viscoelastic diffeomorphisms between preoperative MR and intraoperative CT using modality-independent neighborhood descriptors ( MIND) and aHuber metric for robust registration. The method, called MIND Demons, optimizes a constrained symmetric energy functional incorporating priors on smoothness, geodesics, and invertibility by alternating between Gauss-Newton optimization and Tikhonov regularization in a multiresolution scheme. Registration performance was evaluated for the MIND Demons method with a symmetric energy formulation in comparison to an asymmetric form, and sensitivity to anisotropic MR voxel-size was analyzed in phantom experiments emulating image-guided spine-surgery in comparison to a free-form deformation (FFD) method using local mutual information (LMI). Performance was validated in a clinical study involving 15 patients undergoing intervention of the cervical, thoracic, and lumbar spine. The target registration error (TRE) for the symmetric MIND Demons formulation (1.3 +/- 0.8 mm (median +/- interquartile)) outperformed the asymmetric form (3.6 +/- 4.4 mm). The method demonstrated fairly minor sensitivity to anisotropic MR voxel size, with median TRE ranging 1.3-2.9 mm for MR slice thickness ranging 0.9-9.9 mm, compared to TRE = 3.2-4.1 mm for LMI FFD over the same range. Evaluation in clinical data demonstrated sub-voxel TRE (< 2 mm) in all fifteen cases with realistic deformations that preserved topology with sub-voxel invertibility (0.001 mm) and positive-determinant spatial Jacobians. The approach therefore appears robust against realistic anisotropic resolution characteristics in MR and yields registration accuracy suitable to application in image-guided spine-surgery.
引用
收藏
页码:8276 / 8297
页数:22
相关论文
共 50 条
  • [31] Evaluation of the performance of deformable image registration between planning CT and CBCT images for the pelvic region: comparison between hybrid and intensity-based DIR
    Takayama, Yoshiki
    Kadoya, Noriyuki
    Yamamoto, Takaya
    Ito, Kengo
    Chiba, Mizuki
    Fujiwara, Kousei
    Miyasaka, Yuya
    Dobashi, Suguru
    Sato, Kiyokazu
    Takeda, Ken
    Jingu, Keiichi
    JOURNAL OF RADIATION RESEARCH, 2017, 58 (04) : 567 - 571
  • [32] Registration of MR and CT images of the liver: comparison of voxel similarity and surface based registration algorithms
    Lee, WCC
    Tublin, ME
    Chapman, BE
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2005, 78 (02) : 101 - 114
  • [33] Learning-based deformable image registration for infant MR images in the first year of life
    Hu, Shunbo
    Wei, Lifang
    Gao, Yaozong
    Guo, Yanrong
    Wu, Guorong
    Shen, Dinggang
    MEDICAL PHYSICS, 2017, 44 (01) : 158 - 170
  • [34] Evaluation of accuracy of B-spline transformation-based deformable image registration with different parameter settings for thoracic images
    Kanai, Takayuki
    Kadoya, Noriyuki
    Ito, Kengo
    Onozato, Yusuke
    Cho, Sang Yong
    Kishi, Kazuma
    Dobashi, Suguru
    Umezawa, Rei
    Matsushita, Haruo
    Takeda, Ken
    Jingu, Keiichi
    JOURNAL OF RADIATION RESEARCH, 2014, 55 (06) : 1163 - 1170
  • [35] Clinical feasibility of MR-assisted CT-based cervical brachytherapy using MR-to-CT deformable image registration
    Dyer, Brandon A.
    Yuan, Zilong
    Qiu, Jianfeng
    Shi, Liting
    Wright, Cari
    Benedict, Stanley H.
    Valicenti, Richard
    Mayadev, Jyoti S.
    Rong, Yi
    BRACHYTHERAPY, 2020, 19 (04) : 447 - 456
  • [36] Performance Evaluation of Deformable Image Registration Systems - SmartAdapt® and Velocity™
    Kumar, M. Anil
    Hajare, Raghavendra
    Nath, Bhakti Dev
    Lakshmi, K. K. Sree
    Mahantshetty, Umesh M.
    JOURNAL OF MEDICAL PHYSICS, 2024, 49 (02) : 240 - 249
  • [37] A Gaussian Mixture plus Demons Deformable Registration Method for Cone-Beam CT-Guided Robotic Transoral Base-of-Tongue Surgery
    Reaungamornrat, S.
    Liu, W. P.
    Schafer, S.
    Otake, Y.
    Nithiananthan, S.
    Uneri, A.
    Richmon, J.
    Sorger, J.
    Siewerdsen, J. H.
    Taylor, R. H.
    MEDICAL IMAGING 2013: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING, 2013, 8671
  • [38] Quantitative assessment of intra- and inter-modality deformable image registration of the heart, left ventricle, and thoracic aorta on longitudinal 4D-CT and MR images
    Omidi, Alireza
    Weiss, Elisabeth
    Wilson, John S.
    Rosu-Bubulac, Mihaela
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2022, 23 (02):
  • [39] Deformable registration of preoperative MR and intraoperative long-length tomosynthesis images for guidance of spine surgery via image synthesis
    Huang, Yixuan
    Zhang, Xiaoxuan
    Hu, Yicheng
    Johnston, Ashley R.
    Jones, Craig K.
    Zbijewski, Wojciech B.
    Siewerdsen, Jeffrey H.
    Helm, Patrick A.
    Witham, Timothy F.
    Uneri, Ali
    COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2024, 114
  • [40] Image registration of MR and CT images using a frameless fiducial marker system
    Kremser, C
    Plangger, C
    Bosecke, R
    Pallua, A
    Aichner, F
    Felber, SR
    MAGNETIC RESONANCE IMAGING, 1997, 15 (05) : 579 - 585