A Literature Survey of Ultrasound and Computed Tomography-Based Cardiac Image Registration

Authors

  • Chieng Thion Ming IJN-UTM Cardiovascular Engineering Centre, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Zaid Omar IJN-UTM Cardiovascular Engineering Centre, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Nasrul Humaimi Mahmood IJN-UTM Cardiovascular Engineering Centre, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Suhaini Kadiman National Heart Institute, Jalan Tun Razak, 50400 Kuala Lumpur, Malaysia

DOI:

https://doi.org/10.11113/jt.v74.4672

Abstract

A literature survey of Ultrasound and Computed Tomography (CT) -based cardiac image registration is presented in this article. We aim to provide the reader with a preliminary discussion into the area of cardiac image registration, as well as to briefly describe the major contributions in the field and present collective and comprehensive knowledge as guidelines for beginners in this field to initiate their research. We also highlight the major challenges where CT and Ultrasound are the modalities concerned in fusion and registration tasks. Further, we found that a majority of research in medical image registration are suitably categorized based on these factors: anatomy, imaging modality and image registration methods. Our focus in the article is on Ultrasound-CT image registration of the heart, where numerous algorithms under this scope have been elaborated. Overall, multimodal cardiac image registration offers great benefit for image visualization systems during surgery. It facilitates accurate alignment of the patient’s heart imagery acquired via different imaging sensors, without extensive user involvement and interception. Through registration, the combined anatomical and functional information from multiple modalities may be derived by the medical practitioner to aid in physiological understanding, disease monitoring, clinical treatment and diagnostic purposes.

References

A. P. James, B. V. Dasarathy, B. 2014. Medical Image Fusion: A Survey of the State of the Art. Inf Fusion. 19: 4–19.

T. Russell, L. Joskowicz. 2002. Computer-Integrated Surgery and Medical Robotics. Standard Handbook of Biomedical Engineering. M Kutz, McGraw-Hill Professional. 325–53.

J. Demongeot, J. B. Wendling, J. Mattes, P. Haigron, N. Glade, J. L. Coatrieux. 2003. Multiscale Modeling and Imaging: The Challenges of Biocomplexity. Proceedings of the IEEE. 91(10): 1723–37.

L. Curiel, R. Chopra, K. Hynynen. 2007. Progress in Multimodality Imaging: Truly Simultaneous Ultrasound and Magnetic Resonance Imaging. IEEE transactions on medical imaging. 26(12): 1740–6.

F. P. M. Oliveira, J. M. R. S. Tavares. 2012. Medical Image Registration: A Review. Computer Methods in Biomechanics and Biomedical Engineering. 17(2): 73–93.

Z. Xiong, Y. Zhang. 2010. A Critical Review of Image Registration Methods. International Journal of Image and Data Fusion. 1(2): 137–58.

T. McInerney, D. Terzopoulos. 1996. Deformable Models in Medical Image Analysis: A Survey. Med. Imag. Anal. 1(2): 91–108.

C. Fookes, M. Bennamoun. 2000. Registration of Three Dimensional Medical Images: Technical Report. Brisbane: Space Centre for Satellite Navigation, School of Electrical and Electronic Systems, Queensland University of Technology.

D. Simon. 1997. What is "Registration" and Why is it so Important in CAOS? Proceedings of the First Joint CVR Med / MRCAS Conference. June: 57–60.

X. Huang, J. Moore, G. Guiraudon, D. L. Jones, D. Bainbridge, J. Ren et al. 2009. Dynamic 2D Ultrasound and 3D CT Image Registration of the Beating Heart. IEEE Transactions on Medical Imaging. 28(8): 1179–89.

L. G. Brown. 1992. A Survey of Image Registration Techniques. ACM Comput. Surv. 24(4): 325–376.

P. A. Van den Elsen, E.–J. D. Pol, M. A. Viergever. 1993. Medical Image Matching-A Review with Classification. IEEE Engineering in Medicine and Biology Magazine. 12(1): 26–39.

J. B. Antoine Maintz, M. A. Viergever. 1996. An Overview of Medical Image Registration Methods. Symposium of the Belgian Hospital Physicists Association.

D. L. G. Hill, P. G. Batchelor, M. Holden, D. J. Hawkes. 2001. Medical Image Registration. Physics in Medicine Aand Biology. 46(3): 1–45.

J. V. Hajnal, D. L. G. Hill, D. J. Hawkes. 2001. Medical Image Registration. London: CRC Press

M. Sonka, J. M. Fitzpatrick. 2000. Handbook of Medical Imaging: Medical Image Processing and Analysis. 2: 375–435.

I. Bankman. 2008. Handbook of Medical Image Processing and Analysis: Elsevier Science.

A. F. Frangi, W. J. Niessen, M. A. Viergever. 2001. Three-dimensional Modeling for Functional Analysis of Cardiac Images, A Review. IEEE Transactions on Medical Imaging. 20(1): 2–5.

M. A. Audette, F. P. Ferrie, T. M. Peters. 2000. An Algorithmic Overview of Surface Registration Techniques for Medical Imaging. Medical Image Analysis. 4(3): 201–217.

H. Lester, S. R. Arridge. 1998. A Survey of Hierarchical Nonlinear Medical Image Registration. Pattern Recognition. 32: 129–149.

T. Makela, P. Clarysse, O. Sipila, N. Pauna, Q. C. Pham, T. Katila et al. 2002. A Review of Cardiac Image Registration Methods. IEEE Trans Med Imaging. 21(9): 1011–21.

C. Hua-mei, P. K. Varshney. 2003. Mutual Information-based CT-MR Brain Image Registration Using Generalized Partial Volume Joint Histogram Estimation. IEEE Transactions on Medical Imaging. 22(9): 1111–1119.

J. Ashburner, K. Friston. 1997. Multimodal Image Coregistration and Partitioning—A Unified Framework. NeuroImage. 6(3): 209–217.

F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, P. Suetens. 1997. Multimodality Image Registration by Maximization of Mutual Information. IEEE Transactions on Medical Imaging. 16(2): 187–198.

A. Klein, S. S. Ghosh, B. Avants, B. T. T. Yeo, B. Fischl, B. Ardekani et al. 2010. Evaluation of Volume-based and Surface-based Brain Image Registration Methods. NeuroImage. 51(1): 214–220.

J. P. W. Pluim, J. B. Antoine Maintz, M. A. Viergever. 2000. Interpolation Artefacts in Mutual Information-Based Image Registration. Computer Vision and Image Understanding. 77(2): 211–232.

H. J. Johnson, G. E. Christensen. 2002. Consistent Landmark And Intensity-based Image Registration. IEEE Transactions on Medical Imaging. 21(5): 450–461.

Y. Xie, M. Chao, L. Xing. 2009. Tissue Feature-Based and Segmented Deformable Image Registration for Improved Modeling of Shear Movement of Lungs. International Journal of Radiation Oncology Biology Physics. 74(4): 1256–1265.

J. Ehrhardt, R. Werner, A. Schmidt-Richberg, H. Handels. 2011. Statistical Modeling of 4D Respiratory Lung Motion Using Diffeomorphic Image Registration. IEEE Transactions on Medical Imaging. 30(2): 251–265.

K. Ding, Y. Yin, K. Cao, G. Christensen, C. –L. Lin, E. Hoffman et al. 2009. Evaluation of Lobar Biomechanics during Respiration Using Image Registration. Medical Image Computing and Computer-Assisted Intervention–MICCAI. 5761: 739–746.

D. Mattes, D. R. Haynor, H. Vesselle, T. K. Lewellen, W. Eubank. 2003. PET-CT Image Registration in the Chest Using Free-form Deformations. IEEE Transactions on Medical Imaging. 22(1): 120–128.

E. C. Richard Castillo, R. Guerra, V. E. Johnson, T. McPhail, A. K. Garg, T. Guerrero. 2009. A Framework For Evaluation Of Deformable Image Registration Spatial Accuracy Using Large Landmark Point Sets. Physics in Medicine and Biology. 54(7).

J. M. Adil Al-Mayah, M. Velec, K. Brock. 2011. Toward Efficient Biomechanical-based Deformable Image Registration of Lungs for Image-Guided Radiotherapy. Physics in Medicine and Biology. 56(15).

A. Leroy, P. Mozer, Y. Payan, J. Troccaz. 2004. Rigid Registration of Freehand 3D Ultrasound and CT-Scan Kidney Images. Medical Image Computing and Computer-Assisted Intervention–MICCAI 2004. 3216: 837–844.

F. G. Zöllner, R. Sance, P. Rogelj, M. J. Ledesma-Carbayo, J. Rørvik, A. Santos et al. 2009. Assessment of 3D DCE-MRI of the Kidneys Using Non-rigid Image Registration and Segmentation of Voxel Time Courses. Computerized Medical Imaging and Graphics. 33(3): 171–181.

W. Wein, S. Brunke, A. Khamene, M. R. Callstrom, N. Navab. 2008. Automatic CT-Ultrasound Registration for Diagnostic Imaging and Image-guided Intervention. Medical Image Analysis. 12(5): 577–585.

M. Spiegel, D. A. Hahn, V. Daum, J. Wasza, J. Hornegger. 2009. Segmentation of Kidneys Using a New Active Shape Model Generation Technique Based on Non-rigid Image Registration. Computerized Medical Imaging and Graphics. 33(1): 29–39.

A. Carrillo, J. L. Duerk, J. S. Lewin, D. L. Wilson. 2000. Semiautomatic 3-D Image Registration as Applied to Interventional MRI Liver Cancer Treatment. IEEE Transactions on Medical Imaging. 19(3): 175–185.

G. P. Penney, J. M. Blackall, M. S. Hamady, T. Sabharwal, A. Adam, D. J. Hawkes. 2004. Registration of Freehand 3D Ultrasound and Magnetic Resonance Liver Images. Medical Image Analysis. 8(1): 81–91.

W. V. Vogel, J. A. van Dalen, B. Wiering, H. Huisman, Corstens, H. Frans, T. J. Ruers, W. J. Oyen. 2007. Evaluation of Image Registration in PET/CT of the Liver and Recommendations for Optimized Imgaing. The Journal of Nuclear Medicine. 48(6): 910–919.

A. J. Herline, J. L. Herring, J. D. Stefansic, W. C. Chapman, R. L. Galloway, B. M. Dawant. 2000. Surface Registration for Use in Interactive, Image-Guided Liver Surgery. Computer Aided Surgery. 5(1): 11–17.

O. Sadowsky, G. Chintalapani, R. Taylor. 2007. Deformable 2D-3D Registration of the Pelvis with a Limited Field of View, Using Shape Statistics. Medical Image Computing and Computer-Assisted Intervention–MICCAI 2007. 4792: 519–526.

D. C. Barratt, C. S. K. Chan, P. J. Edwards, G. P. Penney, M. Slomczykowski, T. J. Carter et al. 2008. Instantiation and Registration of Statistical Shape Models of the Femur and Pelvis Using 3D Ultrasound Imaging. Medical Image Analysis. 12(3): 358–374.

V. Tavakoli, A. A. Amini. 2013. A Survey of Shaped-based Registration and Segmentation Techniques for Cardiac Images. Comput. Vis. Image Underst. 117(9): 966–989.

G. J. Klein, R. H. Huesman. 2002. Four-Dimensional Processing of Deformable Cardiac PET Data. Med Image Anal. 6(1): 29–46.

G. J. Tortora, B. H. Derrickson. 2009. Principles of Anatomy and Physiology: Maintenance and Continuity of the Human Body. Volume 2. John Wiley & Sons Incorporated.

H. Yuxuan, Q. Zhongpan, S. Zhijun. 2011. 3D Reconstruction and Visualization from 2D CT Images. International Symposium on IT in Medicine and Education (ITME). 2: 153–157.

National Heart Institute of Malaysia, IJN. 2014. Computed Tomography Cardiac Image Dataset.

N. Sheikh. 2006. Medium Resolution Computed Tomography Through Phosphor Screen Detector and 3D Image Analysis.

L. F. Herbert. 2004. Drawbacks and Limitations of Computed Tomography. Texas Heart Institute Journal. 345–348.

http://www.philips.com.my/healthcare-product/HC795052/ie33-xmatrix-ultrasound-machine

Retrieved on 1st February 2015.

A. Fenster, D. B. Downey, H. Neale Cardinal. 2001. Three-dimensional Ultrasound Imaging. Physics in Medicine and Biology. 46(5): 67–99.

O. V. Michailovich, A. Tannenbaum. 2006. Despeckling of Medical Ultrasound Images. IEEE Transactions on Ultrasound Ferroelectrics Freqency Control. 53(1): 64–78.

P. N. Burns. Introduction to the Physical Principles of Ultrasound Imaging and Doppler. Fundamentals in Medical Biophysics.

G. Kossoff. 2000. Basic Physics and Imaging Characteristics of Ultrasound. World Journal of Surgery. 24: 134–142.

V. R. S. Mani, D. S. Rivazhagan. 2013. Survey of Medical Image Registration. Journal of Biomedical Engineering and Technology. 1(2): 8–25.

T. L. Faber, R. W. McColl, R. M. Opperman, J. R. Corbett, R. M. Peshock. 1991. Spatial and Temporal Registration of Cardiac SPECT and MR Images: Methods and Evaluation. Radiology. 179(3): 857–861.

H. Zhong, T. Kanade, D. Schwartzman. 2006. Virtual Touch: An Efficient Registration Method for Catheter Navigation in Left Atrium. Medical Image Computing and Computer-Assisted Intervention: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention. 9(1): 437–44.

Y. Sun, S. Kadoury, Y. Li, M. John, J. Resnick, G. Plambeck, R. Liao, F. Sauer, C. Xu. 2007. Image Guidance of Intracardiac Ultrasound With Fusion of Pre-Operative Images. In Med. Image Comput. Comput. Assist. Interv. Int. Conf. Med. Image Comput. Comput. Assist. Interv 10(1): 60–67.

Z. L. Sandoval, J. L. Dillenseger. 2013. Evaluation of Computed Tomography to Ultrasound 2D Image Registration for Atrial Fibrillation Treatment. Computing in Cardiology Conference (CinC).

P. Lang, M. Rajchl, L. Feng, T. M. Peters. 2011. Towards Model-Enhanced Real-Time Ultrasound Guided Cardiac Interventions. Intelligent Computation and Bio-Medical Instrumentation (ICBMI).

L. Feng, P. Lang, M. Rajchl, E. C. S. Chen, G. Guiraudon, T. M. Peters. 2012. Towards Real-time 3D US-CT Registration on the Beating Heart for Guidance of Minimally Invasive Cardiac Interventions, Proc. SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling.

L. Feng, M. Rajchl, J. White, A. Goela, T. Peters. 2013. Generation of Synthetic 4D Cardiac CT Images for Guidance of Minimally Invasive Beating Heart Interventions. Information Processing in Computer-Assisted Interventions. 7915: 11–20.

Z. Qian, C. Zhiguo, H. Zhongwen, J. Yonghong, W. Xiaoliang. 2014. Joint Image Registration and Fusion for Panchromatic and Multispectral Images. Geoscience and Remote Sensing Letters, IEEE. 12(3): 467–471.

P.A. Legg, P. L. Rosin, D. Marshall, J. E. Morgan. 2008. Incorporating Neighbourhood Feature Derivatives With Mutual Information to Improve Accuracy of Multi-Modal Image Registration. Medical Imaging Understanding and Analysis. 39–43

Downloads

Published

2015-05-28

How to Cite

A Literature Survey of Ultrasound and Computed Tomography-Based Cardiac Image Registration. (2015). Jurnal Teknologi, 74(6). https://doi.org/10.11113/jt.v74.4672