Automatic 2D/2D Registration using Multiresolution Pyramid based Mutual Information in Image Guided Radiation Therapy
Medical image registration is the key technology in image guided radiation therapy (IGRT) systems. On the basis of the previous work on our IGRT prototype with a biorthogonal x-ray imaging system, we described a method focused on the 2D/2D rigid-body registration using multiresolution pyramid based mutual information in this paper. Three key steps were involved in the method ： firstly, four 2D images were obtained including two x-ray projection images and two digital reconstructed radiographies（DRRs ） as the input for the registration ； Secondly, each pair of the corresponding x-ray image and DRR image were matched using multiresolution pyramid based mutual information under the ITK registration framework ； Thirdly, we got the final couch offset through a coordinate transformation by calculating the translations acquired from the two pairs of the images. A simulation example of a parotid gland tumor case and a clinical example of an anthropomorphic head phantom were employed in the verification tests. In addition, the influence of different CT slice thickness were tested. The simulation results showed that the positioning errors were 0.068±0.070, 0.072±0.098, 0.154±0.176mm along three axes which were lateral, longitudinal and vertical. The clinical test indicated that the positioning errors of the planned isocenter were 0.066, 0.07, 2.06mm on average with a CT slice thickness of 2.5mm. It can be concluded that our method with its verified accuracy and robustness can be effectively used in IGRT systems for patient setup.
[1] O. MAINTZ J B A, VIERGEVER M A. A survey of medical image
registration [J]. Medical Image Analysis, 1997, 2(1): 1-2.
[2] Terry S. Yoo. Insight into Images :principles and practice for
segmentation, registration, and image analysis [M]. 2004, 240-241.
[3] Pluim, J.P.W., Maintz, J.B.A, Viergever, M.A. Mutual information based
registration of medical images´╝Üa survey. 2003, 22(8): 986 - 1004.
[4] Li Jia. key technologies in image-guided radiation therapy system
research and an IGRT prototype system implementation[D]. Institute of
Plasma Physics, Chinese Academy of Sciences, 2010.
[5] Song Gang. Hybrid Dose Calculation Research and Program
Development for Accurate Radiotherapy (doctor thesis). Hefei´╝ÜInstitute
of Plasma Physics, Chinese Academy of Sciences, July, 2008, 1-100. (in
Chinese).
[6] Wu Yican, Song Gang, Cao Ruifen et al. Chinese Physics C (HEP & NP),
2008, 32(Suppl. II): 177-182.
[7] LI Guoli. Study on Multi-objective Optimization Algorithm for Inverse
Planning of External Radiation in ARTS (doctor thesis). Hefei: Institute
of Plasma Physics, Chinese Academy of Sciences, July, 2006, 1-100.
[8] Cao Ruifen, Li Guoli, Song Gang etal. Chinese Journal of Radiological
Medicine and Protection, 2007, 27(5):467-470 (in Chinese).
[9] Li Guoli, Song Gang, Wu Yican. Nuclear Technology, 2007, 30(3):
222-226(in Chinese).
[10] Li Guoli, Wu Yican, Zhang Jian. Plasma Science and Technology, 2006,
8(2):234-236.
[11] Li Guoli, Wu Yican, Song Gang, Wang Shifang. Nuclear Physics
Review,2006,23(2): 233-236(in Chinese).
[12] Cao Ruifen, Li Guoli, Wu Yican. Advanced Intelligent Computing
Theories and Applications. 2007, 4682:553-564.
Translation after registration
CT slice ´╝êmm´╝ë
thickness´╝êmm´╝ë X Y Z
2.5 0.066 0.070 2.060
5 0.772 0.980 4.435
10 0.514 1.076 8.393
[13] L. Lemieux, R. Jagoe, D. R. Fish, N. D. Kitchen, and D. G. T. Thomas, "A
patient-to-computed-tomography image registration method based on
digitally reconstructed radiographs," Med. Phys. 21, pp. 1749-1760,
1994.
[14] Daniel B. Russakoff, Torsten Rohlfing, Daniel Rueckert, Fast calculation
of digitally reconstructed radiographs using light fields. Medical Imaging
2003: Image Processing . Proceedings of SPIE Vol. 5032 (2003):
684-695.
[15] Insight Software Consortium. The ITK Software Guide [M/CD]. Second
Edition, Updated for ITK version 2.4, 2005. 315-316.
[16] Maes, F., Vandermeulen, D., Suetens, P. Medical Image Registration
Using Mutual Information. Proceedings of the IEEE. 2003, 91(10): 1699 -
1722.
[17] Frederik Maes, Andre Collignon. Multimodality image registration by
maximization of mutual information[J]. IEEE Transaction on Medical
Imaging. 1997, 16(2):187ÔÇö198.
[18] J. P. Pluim, J. B. A. Maintz, and M. A. Viergever.
Mutual-Information-Based Registration of Medical Images: A Survey.
IEEE Transactions on Medical Imaging. 2003, 22(8):986-1004.
[19] CHEN Y, BROOKS RR, LYENGAR SS, et al. Efficient global
optimization for image registration [J]. IEEE Transaction on Knowledge
and Engineering, 2002, 14 (1):79-92.
[20] Thevenaz, P., Unser, M. Optimization of mutual information for
multiresolution image registration[J]. IEEE Transaction on Image
Processing. 2000, 9(12): 2083 - 2099.
[21] Shanqing Huang, Pengcheng Long, Jia Li. Research on registration and
fusion of images based on ITK and VTK [J]. Computer Application.
2010, 30(1).
[22] Insight Software Consortium. The ITK Software Guide [M/CD]. Second
Edition, Updated for ITK version 2.4, 2005.334-338.
[23] Mi Zhang, Xiaoming Wu, Linghong Zhou. Mattes mutual information
medical image registration based on ITK [J]. Microcomputer Information.
2010, 3-2´╝Ü189-191.
[24] Chen Xin,Martin R Varley,Lik-Kwan Shark,et al.A computationally
efficient method for automatic registration of orthogonal x-ray images
with volumetric CT data[J].Physics in Medicine and Biology, 2008,
53(4):967-983.
[25] Markelj, P., A review of 3D/2D registration methods for image-guided
interventions. Med. Image Anal. (2010),doi:10.1016/j.media.2010.03.005
[26] Jian-Yue Jin, Samuel Ryu, Kathleen Faber, et al. 2D/3D Image fusion for
accurate target localization and evaluation of a mask based stereotactic
system in fractionated stereotactic radiotherapy of cranial lesions. Med.
Phys. Vol. 33, No. 12, 2006. 4557-4560.
[27] Hui Yan, Fang-Fang Yin, and Jae Ho Kim. A phantom study on the
positioning accuracy of the Novalis Body system .Med. Phys. 2003, Vol.
30, No. 12. 3507-3508.
[1] O. MAINTZ J B A, VIERGEVER M A. A survey of medical image
registration [J]. Medical Image Analysis, 1997, 2(1): 1-2.
[2] Terry S. Yoo. Insight into Images :principles and practice for
segmentation, registration, and image analysis [M]. 2004, 240-241.
[3] Pluim, J.P.W., Maintz, J.B.A, Viergever, M.A. Mutual information based
registration of medical images´╝Üa survey. 2003, 22(8): 986 - 1004.
[4] Li Jia. key technologies in image-guided radiation therapy system
research and an IGRT prototype system implementation[D]. Institute of
Plasma Physics, Chinese Academy of Sciences, 2010.
[5] Song Gang. Hybrid Dose Calculation Research and Program
Development for Accurate Radiotherapy (doctor thesis). Hefei´╝ÜInstitute
of Plasma Physics, Chinese Academy of Sciences, July, 2008, 1-100. (in
Chinese).
[6] Wu Yican, Song Gang, Cao Ruifen et al. Chinese Physics C (HEP & NP),
2008, 32(Suppl. II): 177-182.
[7] LI Guoli. Study on Multi-objective Optimization Algorithm for Inverse
Planning of External Radiation in ARTS (doctor thesis). Hefei: Institute
of Plasma Physics, Chinese Academy of Sciences, July, 2006, 1-100.
[8] Cao Ruifen, Li Guoli, Song Gang etal. Chinese Journal of Radiological
Medicine and Protection, 2007, 27(5):467-470 (in Chinese).
[9] Li Guoli, Song Gang, Wu Yican. Nuclear Technology, 2007, 30(3):
222-226(in Chinese).
[10] Li Guoli, Wu Yican, Zhang Jian. Plasma Science and Technology, 2006,
8(2):234-236.
[11] Li Guoli, Wu Yican, Song Gang, Wang Shifang. Nuclear Physics
Review,2006,23(2): 233-236(in Chinese).
[12] Cao Ruifen, Li Guoli, Wu Yican. Advanced Intelligent Computing
Theories and Applications. 2007, 4682:553-564.
Translation after registration
CT slice ´╝êmm´╝ë
thickness´╝êmm´╝ë X Y Z
2.5 0.066 0.070 2.060
5 0.772 0.980 4.435
10 0.514 1.076 8.393
[13] L. Lemieux, R. Jagoe, D. R. Fish, N. D. Kitchen, and D. G. T. Thomas, "A
patient-to-computed-tomography image registration method based on
digitally reconstructed radiographs," Med. Phys. 21, pp. 1749-1760,
1994.
[14] Daniel B. Russakoff, Torsten Rohlfing, Daniel Rueckert, Fast calculation
of digitally reconstructed radiographs using light fields. Medical Imaging
2003: Image Processing . Proceedings of SPIE Vol. 5032 (2003):
684-695.
[15] Insight Software Consortium. The ITK Software Guide [M/CD]. Second
Edition, Updated for ITK version 2.4, 2005. 315-316.
[16] Maes, F., Vandermeulen, D., Suetens, P. Medical Image Registration
Using Mutual Information. Proceedings of the IEEE. 2003, 91(10): 1699 -
1722.
[17] Frederik Maes, Andre Collignon. Multimodality image registration by
maximization of mutual information[J]. IEEE Transaction on Medical
Imaging. 1997, 16(2):187ÔÇö198.
[18] J. P. Pluim, J. B. A. Maintz, and M. A. Viergever.
Mutual-Information-Based Registration of Medical Images: A Survey.
IEEE Transactions on Medical Imaging. 2003, 22(8):986-1004.
[19] CHEN Y, BROOKS RR, LYENGAR SS, et al. Efficient global
optimization for image registration [J]. IEEE Transaction on Knowledge
and Engineering, 2002, 14 (1):79-92.
[20] Thevenaz, P., Unser, M. Optimization of mutual information for
multiresolution image registration[J]. IEEE Transaction on Image
Processing. 2000, 9(12): 2083 - 2099.
[21] Shanqing Huang, Pengcheng Long, Jia Li. Research on registration and
fusion of images based on ITK and VTK [J]. Computer Application.
2010, 30(1).
[22] Insight Software Consortium. The ITK Software Guide [M/CD]. Second
Edition, Updated for ITK version 2.4, 2005.334-338.
[23] Mi Zhang, Xiaoming Wu, Linghong Zhou. Mattes mutual information
medical image registration based on ITK [J]. Microcomputer Information.
2010, 3-2´╝Ü189-191.
[24] Chen Xin,Martin R Varley,Lik-Kwan Shark,et al.A computationally
efficient method for automatic registration of orthogonal x-ray images
with volumetric CT data[J].Physics in Medicine and Biology, 2008,
53(4):967-983.
[25] Markelj, P., A review of 3D/2D registration methods for image-guided
interventions. Med. Image Anal. (2010),doi:10.1016/j.media.2010.03.005
[26] Jian-Yue Jin, Samuel Ryu, Kathleen Faber, et al. 2D/3D Image fusion for
accurate target localization and evaluation of a mask based stereotactic
system in fractionated stereotactic radiotherapy of cranial lesions. Med.
Phys. Vol. 33, No. 12, 2006. 4557-4560.
[27] Hui Yan, Fang-Fang Yin, and Jae Ho Kim. A phantom study on the
positioning accuracy of the Novalis Body system .Med. Phys. 2003, Vol.
30, No. 12. 3507-3508.
@article{"International Journal of Medical, Medicine and Health Sciences:62592", author = "Jing Jia and Shanqing Huang and Fang Liu and Qiang Ren and Gui Li and Mengyun Cheng and Chufeng Jin and Yican Wu", title = "Automatic 2D/2D Registration using Multiresolution Pyramid based Mutual Information in Image Guided Radiation Therapy", abstract = "Medical image registration is the key technology in image guided radiation therapy (IGRT) systems. On the basis of the previous work on our IGRT prototype with a biorthogonal x-ray imaging system, we described a method focused on the 2D/2D rigid-body registration using multiresolution pyramid based mutual information in this paper. Three key steps were involved in the method ： firstly, four 2D images were obtained including two x-ray projection images and two digital reconstructed radiographies（DRRs ） as the input for the registration ； Secondly, each pair of the corresponding x-ray image and DRR image were matched using multiresolution pyramid based mutual information under the ITK registration framework ； Thirdly, we got the final couch offset through a coordinate transformation by calculating the translations acquired from the two pairs of the images. A simulation example of a parotid gland tumor case and a clinical example of an anthropomorphic head phantom were employed in the verification tests. In addition, the influence of different CT slice thickness were tested. The simulation results showed that the positioning errors were 0.068±0.070, 0.072±0.098, 0.154±0.176mm along three axes which were lateral, longitudinal and vertical. The clinical test indicated that the positioning errors of the planned isocenter were 0.066, 0.07, 2.06mm on average with a CT slice thickness of 2.5mm. It can be concluded that our method with its verified accuracy and robustness can be effectively used in IGRT systems for patient setup.
", keywords = "2D/2D registration, image guided radiation therapy, multi resolution pyramid, mutual information.", volume = "5", number = "8", pages = "344-5", }
