CFP last date
20 December 2024
Reseach Article

3D Modeling of X-Ray Images: A Review

by Baishali Goswami, Santanu Kr. Misra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 132 - Number 7
Year of Publication: 2015
Authors: Baishali Goswami, Santanu Kr. Misra
10.5120/ijca2015907566

Baishali Goswami, Santanu Kr. Misra . 3D Modeling of X-Ray Images: A Review. International Journal of Computer Applications. 132, 7 ( December 2015), 40-46. DOI=10.5120/ijca2015907566

@article{ 10.5120/ijca2015907566,
author = { Baishali Goswami, Santanu Kr. Misra },
title = { 3D Modeling of X-Ray Images: A Review },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 132 },
number = { 7 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 40-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume132/number7/23609-2015907566/ },
doi = { 10.5120/ijca2015907566 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:28:43.959965+05:30
%A Baishali Goswami
%A Santanu Kr. Misra
%T 3D Modeling of X-Ray Images: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 132
%N 7
%P 40-46
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Accurate geometrical reconstruction of human bones into three-dimensional(3D) view is currently required for clinical studies such as enabling the radiologists to well analyze the fractures or infections in the bones, evidence of arthritis, presence of dental decays, lung infections etc. CT-scan is commonly used to obtain accurate reconstruction of the human body. However, this method is quite relucent for the patients as it demands a large number of image data sets, typically, more than 100s of images for a single bone to reconstruct. Analysis using MRI are also meant especially to investigate the anatomy and physiology of the body in both health and disease. However, although quite accurate, CT-scan is not an appropriate 3D reconstruction method because of the high irradiating dose, high price and large input data volume. Thus, a 3D model reconstructed from 2D X-ray images can be a useful alternative. The generation of the 3D model is termed as 3D reconstruction from 2D X-Ray images. The reconstruction of the X-ray images can be achieved from both single and multiple X-Ray images. Many researches have been carried out in this field and the reconstruction has been carried out with varying accuracy. This paper presents a review of the existing methods for accurate 3D reconstruction from bi-planar X-rays.

References
  1. Cresson T., Branchaud D., Chav R., Godbout B. and de Guise J.A., ‘3D Shape Reconstruction of bone from two X-ray images using 2D/3D non-rigid registration based on moving least-squares deformation’, Proceedings of SPIE, Vol. 7623, 76230F, doi: 10.1117/12.844098, Page no. 1-9.
  2. Q. Rizqie, C.Pahl, D.E.O. Dewi, M.A. Ayob, I. Maolana, R. Hermawan, R.D. Soetkino, and E. Suprivanto, ‘3D Coordinate Reconstruction from 2D X-ray images for guided lung biopsy’, WSEAS Transactions on Biology and Biomedicine, E-ISSN:2224-2902, Vol. 11, 2014, Page no.133-139.
  3. N. Baka, B.L.Kaptein, M.de Bruijne, T. Van Walsum, J.E.Giphart, W.J. Niessen, B.P.F.Lelieveldt, ‘2D-3D shape reconstruction of the distal femur from stereo X-Ray imaging using statistical shape models,’ Medical Image Analysis 15(2011)840-850, doi:10.1016.
  4. T.Cresson, R.Chav, D. Branchaud, L.Humbert, B.Godbout, B.Aubert, W.Skalli, and J.A.De Guise, ‘Coupling 2D/3D registration method and statistical model to perform 3D Reconstruction from partial X-Ray image data’, 31st Annual International Conference of the IEEE EMBS, September 2-6, 2009, pp.1008-1011.
  5. Moritz Ehlke, Heiko Ramm, Hans Lamecker, Hans-Christian Hege, Stefan Zachow, ‘Fast generation of virtual X-ray images for reconstruction of 3D anatomy, 1077-2626/13
  6. P.E.Galibarov, P.J.Prendergast, A.B.Lennon, ‘A method to reconstruct patient-specific proximal femur surface models from planar pre-operative radiographs’, Medical Engineering and Physics 32(2010)1180-1188, doi:10.1016.
  7. P.Gamage, S.Q.Xie, P.Delmas, P.Xu, ‘3D reconstruction of patient-specific bone models from 2D radiographs for image guided orthopedic surgery’, Digital Image Computing: Techniques and Applications, IEEE, doi: 10.1109, pp.212-216
  8. Oliver Goretzki, ‘3D Reconstruction of medical images using Java3D’, Bachelor Thesis, Luxembourg, 2008-03-16.
  9. Hans Lamecker, Thomas H. Wenckebach, Hans-Christian Hege, ‘Atlas-based 3D shape reconstruction from X-ray images’.
  10. Vikas Karade, Bhallamudi Ravi, ‘3D femur model reconstruction from bi-plane X-Ray images: a novel method based on Laplacian surface deformation’, International journal of CARS, doi: 10.1007/s 11548-014-1097-6
  11. Haithem Boussaid, Samuel Kadourg, Iasonas Kokkinos, Jean-Yves Lazennec, Guoyan Zheng, Nikos Paragios, ‘3D model-based reconstruction of the proximal femur from low-dose biplanar X-Ray images’, BMVC 2011 http://dx.doi.org/10.5244/c.25.35.
  12. Steffan Schumann, Li Liu, Moritz Tannast, Mathias, Bergmann, Lutz-P. Nolte, Guoyan Zheng, ‘An integrated system for 3D hip-joint reconstruction from 2D X-rays: A preliminary validation study’, Annuals of Biomedical Engineering, vol.41, No.10, October 2013, pp.2077-2087, doi: 10.1007/s10439-013-0822-6.
  13. Vu Cong, Huynh, Quang Linh, ‘3D medical image reconstruction’, Biomedical Engineering Department, Faculty of Applied Science, HCMC University of Technology.
  14. Wei Wei, Wang Guorong, Chen Hua, ‘3D reconstruction of a femur shaft using a model and two 2D X-ray images, Proceedings of 2009 4th International Conference on Computer Science and Education, IEEE.
  15. Simmant Prakoonwit, ‘Towards multiple 3D bone-surface identification and reconstruction using few 2D X-ray images for intra-operative applications’, Department of computer science and technology,University of Bedfordshire, UK.
  16. JunHua Zhang, Liang Lv, Xingling Shi, Yuanyuan Wang, Fei Guo, Yufeng Zhang, Hongjian Li, ‘3D Reconstruction of the spine from biplanar radiography based on contour matching using the Hough transform, IEEE Transactions on Biomedical Engineering, Vol.60, No.7, July 2013.
  17. Guoyan Zhang, ‘3D Volumetric intensity reconstruction from 2D X-ray images using partial least-squares regression’, 2013 IEEE 10th International symposium on Biomedical Imaging, pp.1268-1271.
  18. Bin Zhang, Shaobin Sun, Jinwei Sun, Zhiyong Chi, Chunyang Xi, ‘3D Reconstruction method from bi-planar radiography using DLT Algorithm: Application to the femur’, 2010 First International Conference on pervasive computing, Signal processing and applications, IEEE, doi:10.1109/PCSPA.2010.68 pp.251-254.
  19. S.Laporte, W.Skalli, J.A.De Guisse, F.Lavaste and D.Mitton(2003): A Bi-planar reconstruction method based on 2D and 3D contours: Application to the distal femur, Computer Methods in Biomechanics and Biomedical Engineering, 6:1, 1-6.
  20. A. Le Bras, S.Laporte, V.Bousson, D.Mitton, J.A. De Guise, J.D.Laredo, W.Skalli, ‘Personalised 3D-Reconstruction of proximal femur from low-dose digital bi-planar radiographs, International Congress Series 1256(2003)214-219, doi:10.1016/S0531-5131(03)00285-1.
  21. Thomas S.Y.Tang, Randy E.Ellis, ‘2D/3D Deformable registration using a hybrid atlas’, MICCAI 2005, LNCS 3750, pp.223-230, 2005.
  22. Murat Gunay, Mun-Bo Shim, Kenji Shimada, ‘Cost- and time-effective three-dimensional bone-shape reconstruction from X-Ray images’, The International Journal of Medical Robotics and Computer Assisted Surgery 2007; 3:323-335. doi:10.1002/rcs.162.
  23. Stefano Filippi, Barbara Motyl, Camillo Bandera, ‘Analysis of existing methods for 3D modeling of femurs starting from two orthogonal images and development of a script for a commercial software package’, Computer Methods and programs in Biomedicine 89(2008) 76-82, doi:10.1016/j.cmpb.2007.10.011.
  24. D.Mitton, C.Landry, S.Veron, W.Skalli, F. Lavaste, J.A.De Guise, ‘3D Reconstruction method from bi-planar radiography using non-stereo corresponding points and elastic deformable meshes, Medical and Biological Engineering and Computing.2007, vol.38,pp.133-139.
  25. Moon Kyu Lee, Sang Hyuk Lee, Aram Kim, Inchan Youn, Tae Soo Lee, Nahmkeon Hur, Kuiwon Choi,’ The study of femoral 3D reconstruction process based on anatomical parameters using a numerical method’, Journal of Biomechanical Science and Engineering, vol.3, no.3, 2008, doi: 10.1299, pp.443-451.
  26. Guoyan Zheng, Sebastian Gollmer, Steffen Schumann, Xiao Dong, Thomas Feilkas, Miguel A.Gonzalez Ballester, ‘A 2D/3D correspondence building method for reconstruction of a patient-specific 3D bone surface model using point distribution models and calibrated X-Ray images’, Medical Image Analysis 13(2009) 883-899, doi:10.1016/j.media.2008.12.003.
  27. Kyung Koh, Yoon Hyuk Kim, Kyungsoo Kim, Won Man Park,’ Reconstruction of patient-specific femurs using X-ray and sparse CT Images’, Computers in Biology and Medicine 41(2011)421-426, doi:10.1016/j.compbiomed.2011.03.016.
  28. Otomaru I, Nakamoto M, Kagiyama Y, Takao M, Sugano N, Tomiyama N, Tada Y, Sato Y (2012) Automated preoperative planning of femoral stem in total hip arthroplasty from 3D CT data: atlas-based approach and comparative study. Med Image Anal 16(2):415–426.
  29. Ellis RE, Tso CY, Rudan JF, HarrisonMM(1999) A surgical planning and guidance system for high tibial osteotomy. J Comput Aided Surg 4(5):264–274.
  30. Bredbenner TL, Eliason TD, Potter RS, Mason RL, Havill LM, Nicolella DP (2010) Statistical shape modeling describes variation in tibia and femur surface geometry between Control and Incidence groups from the osteoarthritis initiative database. J Biomech 43(9):1780–1786.
  31. Kohonen T (1982) Self-organised formation of topologically correct feature maps. Biol Cybern 43:59–69.
  32. Caponetti L, Fanelli AM (1990) 3D Bone reconstruction from two X-Ray views. In: Proceedings of twelfth annual international conference of the IEEE engineering in medicine and biology society (EMBS 1990); 1990 Nov 1–4; Philadelphia, PA, USA, pp 208–210.
  33. Livyatan, H., Yaniv, Z., Joskowicz, L., 2003. Gradient-based 2D/3D rigid registration of fluoroscopic x-ray to ct. IEEE Transactions on Medical Imaging 22, 1395– 1406.
  34. Fuente M, Schkommodau E, Lutz P,Neuss M,WirtzDC, Radermacher K (2005) 3D reconstruction and navigated removal of femoral bone cement in revision THR based on few fluoroscopic images. In: Proceedings of computer assisted radiology and surgery (CARS 2004); 2005 June 23–26; Chicago, USA, pp 626–631.
  35. Y H Kim, J K Kim, C Choi. Three-dimensional reconstruction of human femur using consecutive computer tomography images and simulated implantation system. J.Med.Eng.Technol, 2004(28): 205–210.
  36. W E Lorensen, H E Cline. Marching cubes: a high resolution 3D surface construction algorithm. Comput Graph, 1987(21): 163–169.
  37. L Caponetti, A M Fanelli. 3D Bone reconstruction from two X-Ray views. Proceedings of Twelfth Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1990: 208–210.
  38. T.A. Nagelhus Hernes, F. Lindseth, T. Selbekk, A. Wollf, O. Vegard Solberg, E. Harg, O.M. Rygh, G. Arne Tangen, I. Rasmussen, S. Augdal, F. Couweleers, G. Unsgaard, Computer-assisted 3D ultrasound-guided neurosurgery: technological contributions, including multimodal registration and advanced display, demonstrating future perspectives, Int. J. Med. Robotics Comput. Assist. Surg. 2 (2006) 45–59.
  39. A. Mitulescu, S. Laporte, C. Boulay, J.A. De Guise and W. Skalli, (2000) “3D reconstruction of the pelvis using NSCP technique” in the Meeting of the International Research Society in Spinal Deformities, Clermont-Ferrand, France, 26–30 May.
  40. S. Coquillart, Extended free-form deformation: a sculpturing tool for 3D geometric modeling, Comput. Graph. 24 (1990) 187–196.
  41. http://www.mathworks.com, accessed on November 18, 2015.
  42. J.W. Fernandez, P. Mithraratne, S.F. Thrupp, M.H. Tawhai, P.J. Hunter, Anatomically based geometric modelling of the musculo-skeletal system and other organs, Biomech. Model Mechanobiol. 2 (2004) 139–155.
  43. J. Yao. A Statistical Bone Density Atlas and Deformable Medical Image Registration. PhD thesis, Johns Hopkins University, 2001.
  44. S. Benameur, M. Mignotte, S. Parent, H. Labelle, W. Skalli, and J. E. Guise. 3D/2D registration and segmentation of scoliotic vertebrae using statistical models. Computerized Medical Imaging and Graphics, 27(5):321–337, 2003.
Index Terms

Computer Science
Information Sciences

Keywords

3D Reconstruction Hough transform Laplacian deformation Contour matching Medical modeling software.