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3D femur model reconstruction from biplane X-ray images: a novel method based on Laplacian surface deformation

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose 

   Conventional methods for 3D bone model reconstruction from CT scans can require high-radiation dose, cost and time. A 3D model generated from 2D X-ray images may be a useful alternative. Reconfiguring a 3D template surface mesh model to match bone shape in orthogonal radiographs is a common technique for 3D reconstruction. A computationally efficient 3D bone modeling algorithm was developed and tested.

Method 

   An algorithm for bone template reconfiguration is proposed, which uses Kohonen self-organizing maps for 2D–3D correspondence between input X-ray images and the template. Laplacian surface deformation is then used for final deformation of the template. In the literature, Laplacian deformation has been shown to perform better than thin-plate splines and free form deformation in terms of computation time and mesh quality. The method was applied to 22 sets of simulated input contours generated from 3D models of the distal femur.

Results 

   An acceptable range of reconstruction error: 1.5 mm of RMS-P2S (root-mean-square point-to-surface) distance and 1.2 mm mean-P2S distance errors was observed based on comparison with the corresponding reference models/ground truth. Computation time for the 3D bone modeling algorithm was less than a minute for each case.

Conclusion 

   The new template reconfiguration algorithm based on Laplacian surface deformation provided acceptable reconstruction accuracy and high computation efficiency for 3D modeling of the distal femur using biplane radiographs. This algorithm may provide a useful option for orthopedic modeling applications.

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References

  1. 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

    Article  PubMed  Google Scholar 

  2. Ellis RE, Tso CY, Rudan JF, Harrison MM (1999) A surgical planning and guidance system for high tibial osteotomy. J Comput Aided Surg 4(5):264–274

    Article  CAS  Google Scholar 

  3. Kim YH, Kim JK, Choi C (2004) Three-dimensional reconstruction of human femur using consecutive computer tomography images and simulated implantation system. J Med Eng Technol 28(5):205–210

    Article  PubMed  Google Scholar 

  4. Zhang B, Sun S, Sun J, Chi Z, Xi C (2010) 3D reconstruction method from biplanar radiography using dlt algorithm: application to the femur. In: Proceedings of 1st international conference on pervasive computing signal processing and applications (PCSPA 2010); 2010 Sep 17–19; Harbin, China, pp 251–254

  5. 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

  6. Fuente M, Schkommodau E, Lutz P, Neuss M, Wirtz DC, 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

  7. Zheng G, Gollmer S, Schumann S, Dong X, Feilkas T, González Ballester MA (2009) 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. Med Image Anal 13(6):883–99

    Article  PubMed  Google Scholar 

  8. Baka N, Kaptein BL, de Bruijne M, van Walsum T, Giphart JE, Niessen WJ, Lelieveldt BP (2011) 2D–3D shape reconstruction of the distal femur from stereo X-ray imaging using statistical shape models. Med Image Anal 15(6):840–850

    Article  CAS  PubMed  Google Scholar 

  9. Tang T, Ellis R (2005) 2D/3D deformable registration using a hybrid atlas. In: Proceedings of medical image computing and computer-assisted intervention (MICCAI 2005); 2005 Oct 26–29; Palm Springs, CA, USA. Springer, Berlin, pp 223–230

  10. Benameur S, Mignotte M, Parent S, Labelle H, Skalli W, de Guise J (2003) 3D/2D registration and segmentation of scoliotic vertebrae using statistical models. Comput Med Imaging Graph 27(5):321–337

    Article  PubMed  Google Scholar 

  11. Zhu Z, Li G (2011) Construction of 3D human distal femoral surface models using a 3D statistical deformable model. J Biomech 44(13):2368–2362

    Google Scholar 

  12. Fleute M, Lavallée S (1999) Nonrigid 3-D/2-D registration of images using statistical models. In: Proceedings of the second international conference on medical image computing and computer-assisted intervention (MICCAI ’99), 1999, pp 138–147

  13. Hraiech N, Boichon C, Rochette M, Marchal T, Horner M (2010) Statistical shape modeling of femurs using morphing and principal component analysis. J Med Devices 4(2):027534–027534

  14. 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

    Article  PubMed Central  PubMed  Google Scholar 

  15. Ehlke M, Ramm H, Lamecker H, Hege HC, Zachow S (2013) Fast generation of virtual X-ray images for reconstruction of 3D anatomy. IEEE Trans Vis Comp Graph 19(12):2673–2682

  16. Laporte S, Skalli W, de Guise JA, Lavaste F, Mitton D (2003) A biplanar reconstruction method based on 2D and 3D contours: application to the distal femur. Comput Methods Biomech Biomed Eng 6(1):1–6

  17. Le Bras A, Laporte S, Bousson V, Mitton D, De Guise JA, Laredo JD, Skalli W (2004) 3D reconstruction of the proximal femur with low-dose digital stereoradiography. Comput Aided Surg 9(3):51–57

  18. Gunay M, Shim MB, Shimada K (2007) Cost- and time-effective three-dimensional bone-shape reconstruction from X-ray images. Int J Med Robot 3(4):323–335

    Article  PubMed  Google Scholar 

  19. Lee MK, Lee SH, Kim A, Youn I, Lee TS, Hur N, Choi K (2008) The study of femoral 3D reconstruction process based on anatomical parameters using a numerical method. J Biomech Sci Eng 3(3):443–451

    Article  Google Scholar 

  20. Filippi S, Motyl B, Bandera C (2008) Analysis of existing methods for 3D modeling of femurs starting from two orthogonal images and development of a script for a commercial software package. Comput Methods Prog Biomed 89(1):76–82

    Article  Google Scholar 

  21. Koh K, Kim YH, Kim K, Park WM (2011) Reconstruction of patient-specific femurs using X-ray and sparse CT images. Comput Biol Med 41(7):421–426

    Article  PubMed  Google Scholar 

  22. Feng J, Shao J, Jin X, Peng Q, Forrest AR (2006) Multiresolution free-form deformation with subdivision surface of arbitrary topology. Visual Comput 22(1):28–42

    Article  Google Scholar 

  23. Gamage P, Xie, SQ, Delmas, P.; Xu, P (2009) 3D reconstruction of patient specific bone models from 2D radiographs for image guided orthopedic surgery. In: Proceedings of international conference on digital image computing: techniques and applications (DICTA 2009), 2009 Dec 1–3; Melbourne, VIC, pp 212–216

  24. Masuda H, Yoshioka Y, Furukawa Y (2007) Preserving form features in interactive mesh deformation. Comput Aided Design 39(5):361–368

  25. Zhang S, Huang J, Metaxax D (2011) Robust mesh editing using Laplacian coordinates. Graph Model 73(1):10–19

    Article  Google Scholar 

  26. Zhang S, Xiaoxu W, Metaxas D, Ting C, Axel L (2009) LV surface reconstruction from sparse TMRI using Laplacian surface deformation and optimization. In Proceedings of international symposium of biomedical imaging: from nano to macro (ISBI 2009) 2009 Jun 28–Jul 1, Boston, pp 698–701

  27. Heimann T, Meinzer HP (2009) Statistical shape models for 3D medical image segmentation: a review. Med Image Anal 13(4):543–563

    Article  PubMed  Google Scholar 

  28. Kohonen T (1982) Self-organised formation of topologically correct feature maps. Biol Cybern 43:59–69

    Article  Google Scholar 

  29. Ferrarini L, Olofsen H, Palm WM, van Buchem MA, Reiber JH, Admiraal-Behloul F (2007) GAMEs: growing and adaptive meshes for fully automatic shape modeling and analysis. Med Image Anal 11(3):302–314

    Article  PubMed  Google Scholar 

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Acknowledgments

The authors would like to thank Dr. Vijay Shetty (Hiranandani Hospital, Mumbai), Dr. Raju Sharma and Dr. Devasenathipathy (AIIMS, Delhi) for providing the medical imaging data for the study. The authors would also like to thank Mr. Anurag Khaire (M.Tech, IIT-Bombay, India), Mr. Darshan Shah (M.Tech, IIT-Bombay, India) and Mrs. Hepsiba Seeli (Research Assistant, IIT-Bombay) for assisting in creating 3D models from the CT data.

Conflict of interest

Vikas Karade and Bhallamudi Ravi declare that they have no conflict of interest.

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Karade, V., Ravi, B. 3D femur model reconstruction from biplane X-ray images: a novel method based on Laplacian surface deformation. Int J CARS 10, 473–485 (2015). https://doi.org/10.1007/s11548-014-1097-6

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  • DOI: https://doi.org/10.1007/s11548-014-1097-6

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