MAP-MRF based similarity measures for intensity-based 2D-3D registration

被引：0
|
作者：
Zheng, G. [1 ]
Zhang, X. [1 ]
机构：
[1] Univ Bern, ISTB, MEM Res Ctr, CH-3012 Bern, Switzerland
来源：
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY | 2006年 / 1卷
关键词：
2D-3D registration; Similarity measure; Markov random field (MRF); Bayes theorem; Maximum a posterior (MAP);
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D-3D registration of X-ray fluoroscopy to CT images This paper presents a unifying MAP-MRF framework for rationally deriving point similarity measures based on Bayes theorem. Three new similarity measures derived from this framework are presented and evaluated using a phantom and a human cadaveric specimen. Their behaviours are compared with other well-known similarity measures and the comparison results are reported. The optimization of each individual similarity measure derived from this framework leads to optimal registration. We report their capture ranges, converging speeds, and registration accuracies.
引用
收藏
页码：50 / 53
页数：4
相关论文
共 50 条
  • [1] A unifying MAP-MRF framework for deriving new point similarity measures for intensity-based 2D-3D registration
    Zheng, Guoyan
    Zhang, Xuan
    18TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2, PROCEEDINGS, 2006, : 1181 - +
  • [2] Evaluation of similarity measures for use in the intensity-based rigid 2D-3D registration for patient positioning in radiotherapy
    Wu, Jian
    Kim, Minho
    Peters, Jorg
    Chung, Heeteak
    Samant, Sanjiv S.
    MEDICAL PHYSICS, 2009, 36 (12) : 5391 - 5403
  • [3] Multilevel 2D-3D Intensity-Based Image Registration
    Lange, Annkristin
    Heldmann, Stefan
    BIOMEDICAL IMAGE REGISTRATION (WBIR 2020), 2020, 12120 : 57 - 66
  • [4] Evaluation of a stochastic approach to 2D-3D intensity-based registration
    Aouadi, S.
    Sarry, L.
    2007 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-16, 2007, : 6388 - 6391
  • [5] A class of novel point similarity measures based on MAP-MRF framework for 2D-3D registation of X-ray fluoroscopy to CT images
    Zheng, Guoyan
    Zhang, Xuan
    Nolte, Lutz-Peter
    2006 3RD IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: MACRO TO NANO, VOLS 1-3, 2006, : 438 - +
  • [6] Markov Random Field Optimization for Intensity-based 2D-3D Registration
    Zikic, Darko
    Glocker, Ben
    Kutter, Oliver
    Groher, Martin
    Komodakis, Nikos
    Khamene, Ali
    Paragios, Nikos
    Navab, Nassir
    MEDICAL IMAGING 2010: IMAGE PROCESSING, 2010, 7623
  • [7] Intensity-based 2D-3D registration for an ACL reconstruction navigation system
    Guo, Na
    Yang, Biao
    Ji, Xuquan
    Wang, Yuhan
    Hu, Lei
    Wang, Tianmiao
    INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY, 2019, 15 (04):
  • [8] Intensity-based similarity measures evaluation for CT to ultrasound 2D registration
    Sandoval, Z.
    Dillenseger, J. -L.
    IRBM, 2013, 34 (4-5) : 278 - 282
  • [9] Intensity-based 2D-3D spine image registration incorporating one fiducial marker
    Russakoff, DB
    Rohlfing, T
    Shahidi, R
    Kim, DH
    Adler, JR
    Maurer, CR
    MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2003, PT 1, 2003, 2878 : 287 - 294
  • [10] Intensity-based 2D-3D spine image registration incorporating a single fiducial marker
    Russakoff, DB
    Rohlfing, T
    Adler, JR
    Maurer, CR
    ACADEMIC RADIOLOGY, 2005, 12 (01) : 37 - 50
12345