Reconstructing the 3D shape and bone mineral density distribution of the proximal femur from dual-energy x-ray absorptiometry

IEEE Transactions on Medical Imaging

Volumn 30, Issue 12, 2011, Pages 2101-2114

  Whitmarsh, Tristan ^a,b   Humbert, Ludovic ^a,b   De Craene, Mathieu ^a,b   Del Rio Barquero, Luis M ^c   Frangi, Alejandro F ^a,b  

^a UNIVERSITAT POMPEU FABRA   (Spain)

^b BIOMATERIALES Y NANOMEDICINA CIBER BBN   (Spain)

^c CETIR Grup Medic   (Spain)

Author keywords

Active appearance model; active shape model; deformable models; image reconstruction; image registration

Indexed keywords

3-D SHAPE; ACTIVE APPEARANCE MODELS; ACTIVE SHAPE MODELS; BONE MINERAL DENSITY; CLINICAL ROUTINE; DEFORMABLE MODELS; DUAL-ENERGY X-RAY ABSORPTIOMETRY; FRACTURE RISKS; INTENSITY-BASED; LOW COSTS; LOW RADIATION; PROXIMAL FEMUR; QUANTITATIVE COMPUTED TOMOGRAPHIES; REGISTRATION PROCESS; STATISTICAL MODELS; TWO-DIMENSIONALITY;

BONE; COMPUTERIZED TOMOGRAPHY; FACE RECOGNITION; IMAGE RECONSTRUCTION; IMAGE REGISTRATION; LIGHT ABSORPTION; RISK ASSESSMENT; SILICATE MINERALS; TOMOGRAPHY;

THREE DIMENSIONAL;

ADULT; AGED; ARTICLE; BONE DENSITY; FEMALE; FEMUR; HISTOLOGY; HUMAN; IMAGE PROCESSING; IMAGE QUALITY; INSTRUMENTATION; MALE; METHODOLOGY; MIDDLE AGED; PHOTON ABSORPTIOMETRY; PHYSIOLOGY; RADIOGRAPHY; REPRODUCIBILITY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ABSORPTIOMETRY, PHOTON; ADULT; AGED; BONE DENSITY; FEMALE; FEMUR; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; LINEAR MODELS; MALE; MIDDLE AGED; PHANTOMS, IMAGING; REPRODUCIBILITY OF RESULTS;

EID: 82455164550     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2011.2163074     Document Type: Article

References (52)

1. WHO, Prevention and management of osteoporosis World Health Organization Technical Rep. 921, 2003.
2. FRAX WHO Fracture Risk Assessment Tool [Online]. Available: http://www.shef.ac.uk/FRAX
3. X. Cheng, G. Lowet, S. Boonen, P. Nicholson, P. Brys, J. Nijs, and J. Dequeker, "Assessment of the strength of proximal femur in vitro: Relationship to femoral bone mineral density and femoral geometry," Bone, vol. 20, no. 3, pp. 213-218, Mar. 1997. (Pubitemid 27141832)
4. T. F. Lang, J. H. Keyak, M. W. Heitz, P. Augat, Y. Lu, A. Mathur, and H. K. Genant, "Volumetric quantitative computed tomography of the proximal femur: Precision and relation to bone strength," Bone, vol. 21, no. 1, pp. 101-108, 1997. (Pubitemid 27341746)
5. V. Bousson, A. Le Le Bras, F. Roqueplan,Y.Kang,D.Mitton, S. Kolta, C. Bergot, W. Skalli, E. Vicaut, W. Kalender, K. Engelke, and J.-D. Laredo, "Volumetric quantitative computed tomography of the proximal femur: Relationships linking geometric and densitometric variables to bone strength. Role for compact bone," Osteoporosis Int., vol. 17, pp. 855-864, 2006. (Pubitemid 43781499)
6. V. D. Bousson, J. Adams, K. Engelke, M. Aout, M. Cohen-Solal, C. Bergot, D. Haguenauer, D. Goldberg, K. Champion, R. Aksouh, E. Vicaut, and J.-D. Laredo, "In vivo discrimination of hip fracture with quantitative computed tomography: Results from the prospective European Femur Fracture Study (EFFECT)," J. Bone Mineral Res., vol. 26, no. 4, pp. 881-893, 2011.
7. A. Le Bras, S. Laporte, V. Bousson, D. Mitton, J. A. De Guise, J. D. Laredo, and W. Skalli, "Personalised 3D reconstruction of proximal femur from low-dose digital biplanar radiographs," Int. Congress Series, vol. 1256, pp. 214-219, Jun. 2003.
8. A. Baudoin,W. Skalli, J. de Guise, and D.Mitton, "Parametric subjectspecific model for in vivo 3D reconstruction using bi-planar X-rays: Application to the upper femoral extremity," Med. Biol. Eng. Comput., vol. 46, no. 8, pp. 799-805, Aug. 2008.
9. S. Kolta, A. Le Bras, D.Mitton, V. Bousson, J. A. De Guise, J. Fechtenbaum, J. D. Laredo, C. Roux, and W. Skalli, "Three-dimensional X-ray absorptiometry (3D-XA): Amethod for reconstruction of human bones using a dual X-ray absorptiometry device," Osteoporosis Int., vol. 16, no. 8, pp. 969-976, 2005. (Pubitemid 41127107)
10. C. M. Langton, S. Pisharody, and J. H. Keyak, "Generation of a 3D proximal femur shape from a single projection 2D radiographic image," Osteoporosis Int., vol. 20, no. 3, pp. 455-461, Mar. 2009.
11. R.Kurazume, K. Nakamura, T.Okada,Y. Sato,N. Sugano, T.Koyama, Y. Iwashita, and T. Hasegawa, "3D reconstruction of a femoral shape using a parametric model and two 2D fluoroscopic images," Comput. Vis. Image Understand., vol. 113, no. 2, pp. 202-211, 2009.
12. G. Zheng, S. Gollmer, S. Schumann, X. Dong, T. Feilkas, andM. A. G. 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," Med. Image Anal., vol. 13, no. 6, pp. 883-899, 2009.
13. M. Fleute, S. Lavallée, and L. Desbat, "Integrated approach for matching statistical shape models with intra-operative 2D and 3D data," in Med. Image Computing Computer-Assisted Intervent., 2002, pp. 364-372.
14. N. Baka, W. Niessen, B. Kaptein, T. van Walsum, L. Ferrarini, J. Reiber, and B. Lelieveldt, "Correspondence free 3D statistical shape model fitting to sparse x-ray projections," in Proc. SPIE Med. Imag. 2010: Image Process., San Diego, CA.
15. G. Zheng, "Statistical deformable model-based reconstruction of a patient- specific surface model from single standard x-ray radiograph," in Proceedings of the 13th International Conference on Computer Analysis of Images and Pattern, Heidelberg, Germany, 2009, pp. 672-679, Springer-Verlag.
16. J. Yao and R. H. Taylor, "Non-rigid registration and correspondence finding in medical image analysis using multiple-layer flexible mesh template matching," Int. J. Pattern Recognit. Artif. Intell., vol. 17, no. 7, pp. 1145-1165, 2003.
17. L. Belenguer-Querol, P. Buechler, D. Rueckert, L. Nolte, and M. Gonzalez- Ballester, "Statistical finite element model for bone shape and biomechanical properties," in Med. Image Computing Computer-Assisted Intervent., Oct. 2006, pp. 405-411. (Pubitemid 44609131)
18. K. Fritscher, A. Grünerbl, and R. Schubert, "3D image segmentation using combined shape-intensity prior models," Int. J. Comput. Assist. Radiol. Surg., vol. 1, no. 6, pp. 341-350, Apr. 2007.
19. B. Schuler, K. D. Fritscher, V. Kuhn, F. Eckstein, and R. Schubert, "Using a statistical appearance model to predict the fracture load of the proximal femur," in Proc. SPIE Med. Imag. 2009: Visualizat., Image-Guided Procedures, Model., 2009, vol. 7261, no. 1, p. 72610W.
20. P. Steininger, K. D. Fritscher, G. Kofler, B. Schuler, M. Häni, K. Schwieger, and R. Schubert, "Comparison of different metrics for appearance-model-based 2D/3D-registration with X-ray images," in Bildverarbeitung für die Medizin, 2008, pp. 122-126.
21. A. Hurvitz and L. Joskowicz, "Registration of a CT-like atlas to fluoroscopic X-ray images using intensity correspondences," Int. J. Comput. Assist. Radiol. Surg., vol. 3, no. 6, pp. 493-504, Dec. 2008.
22. P. Markelj, D. Tomazevic, B. Likar, and F. Pernus, "A review of 3D/2D registration methods for image-guided interventions," Med. Image Anal. 2010, to be published.
23. O.Ahmad, K. Ramamurthi, K. E.Wilson, K. Engelke, R. L. Prince, and R. H. Taylor, "Volumetric DXA (VXA)-A new method to extract 3D information from multiple in vivo DXA images," J. Bone Mineral Res., vol. 25, no. 12, pp. 2744-2751, Dec. 2010.
24. J. Yao and R. Taylor, "Deformable registration between a statistical bone density atlas and X-ray images," in Proc. CAOS Int., 2002, pp. 168-169.
25. O. Sadowsky, J. Lee, E. Sutter, S. Wall, J. Prince, and R. Taylor, "Hybrid cone-beam tomographic reconstruction: Incorporation of prior anatomical models to compensate for missing data," IEEE Trans. Med. Imag., vol. 30, no. 1, pp. 69-83, Jan. 2011.
26. T.Whitmarsh, L. Humbert, M. S.D. Craene, L. M. del Río Barquero,K. Fritscher, R. Schubert, F. Eckstein, T. M. Link, and A. F. Frangi, "3D bone mineral density distribution and shape reconstruction of the proximal femur from a single simulated DXA image: An in vitro study," in Proc. SPIE Med. Imag. 2010: Image Process., 2010, vol. 7623, no. 1, p. 76234U.
27. T. F. Cootes, G. J. Edwards, and C. J. Taylor, "Active appearance models," in Eur. Conf. Comput. Vis., 1998, vol. 2, pp. 484-498. (Pubitemid 128093046)
28. A. Frangi, D. Rueckert, J. Schnabel, and W. Niessen, "Automatic construction ofmultiple-object three-dimensional statistical shapemodels: Application to cardiacmodeling," IEEE Trans.Med. Imag., vol. 21, no. 9, pp. 1151-1166, Sep. 2002.
29. J. Pettersson, M. Borga, and H. Knutsson, "Some issues on the segmentation of the femur in CT data," in Proc. SSBA Symp. Image Anal., Mar. 2004, pp. 158-161.
30. T. Yoo, M. J. Ackerman, W. E. Lorensen, W. Schroeder, V. Chalana, S. Aylward, and D. Metaxes, "Engineering and algorithm design for an image processing API: A technical report on ITK-The insight toolkit," in Proc. Med. Meets Virtual Reality, 2002, pp. 586-592.
31. P.A.Yushkevich, J. Piven, H. C. Hazlett,R.G. Smith, S.Ho, J. C. Gee, and G.Gerig, "User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability," NeuroImage vol. 31, no. 3, pp. 1116-1128, 2006. (Pubitemid 43851334)
32. W. Press, B. Flannery, S. Teukolsky, and W. Vetterling, Numerical Recipes in C: The Art of Scientific Computing. Cambridge, U.K.: Cambridge Univ. Press, 1992.
33. C. Meyer, J. Boes, B. Kim, and P. Bland, "Probabilistic brain atlas construction: Thin-plate spline warping via maximization of mutual information," in Medical Image Computing and Computer-Assisted Intervention, ser. Lecture Notes in Computer Science, C. Taylor and A. Colchester, Eds. Berlin, Germany: Springer, 1999, vol. 1679, pp. 631-637.
34. H. Hoppe, "New quadric metric for simplifying meshes with appearance attributes," in Proc. 10th IEEE Visualizat. Conf.,Washington, DC, Oct. 1999, p. 59.
35. A. T. Brooks, "Improvements to the itk::KernelTransform and Subclasses," Insight J., Jan. 2007.
36. C. Zhu, R. H. Byrd, P. Lu, and J.Nocedal, "Algorithm778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization," ACM Trans. Math. Software, vol. 23, no. 4, pp. 550-560, 1997. (Pubitemid 127447768)
37. D. Mattes, D. Haynor, H. Vesselle, T. Lewellen, and W. Eubank, "PET-CT image registration in the chest using free-form deformations," IEEE Trans. Med. Imag., vol. 22, no. 1, pp. 120-128, Jan. 2003.
38. C. Lorenz and N. Krahnstöver, "Generation of point-based 3D statistical shape models for anatomical objects,"Comput. Vis. ImageUnderstand., vol. 77, no. 9, pp. 175-191, 2000. (Pubitemid 30557366)
39. J.-M. Peyrat, M. Sermesant, X. Pennec, H. Delingette, C. Xu, E. R. McVeigh, andN.Ayache, "Statistical comparison of cardiac fibre architectures," in Proc. Functional Imag. Model. Heart, 2007, pp. 413-423. (Pubitemid 47289913)
40. A. Guimond, J. Meunier, and J.-P. Thirion, "Average brain models: A convergence study," Comput. Vis. Image Understand., vol. 77, no. 9, pp. 192-210, Feb. 2000. (Pubitemid 30557367)
41. S. Yamakawa and K. Shimada, "Removing self intersections of a triangular mesh by edge swapping, edge hammering, and face lifting," in Med. Image Computing Computer-Assisted Intervent., 1998, pp. 1205-1212.
42. G. Chintalapani, L. Ellingsen, O. Sadowsky, J. Prince, and R. Taylor, "Statistical atlases of bone anatomy: Construction, iterative improvement and validation," in Med. Image Computing Computer-Assisted Intervent., 2007, pp. 499-506.
43. R. B. Cattell, "The scree test for the number of factors," Multivariate Behavioral Res., vol. 1, no. 2, pp. 245-276, 1966.
44. A. Burghardt, G. Kazakia, T. Link, and S.Majumdar, "Automated simulation of areal bone mineral density assessment in the distal radius from high-resolution peripheral quantitative computed tomography," Osteoporosis Int., vol. 20, no. 12, pp. 2017-2024, Dec. 2009.
45. B. Khoo, K. Brown, C. Cann, K. Zhu, S. Henzell, V. Low, S. Gustafsson, R. Price, and R. Prince, "Comparison of QCT-derived and DXA-derived areal bone mineral density and T scores," Osteoporosis Int., vol. 20, no. 9, pp. 1539-1545, Sep. 2009.
46. K. Fritscher, B. Schuler, T. Link, F. Eckstein, N. Suhm, M. Hänni, C. Hengg, and R. Schubert, "Prediction of biomechanical parameters of the proximal femur using statistical appearance models and support vector regression," in Med. Image Computing Computer-Assisted Intervent., 2008, pp. 568-575.
47. D. M. Black, M. L. Bouxsein, L.M. Marshall, S. R. Cummings, T. F. Lang, J. A. Cauley, K. E. Ensrud, C. M. Nielson, and E. S. Orwoll, "Proximal femoral structure and the prediction of hip fracture in men: A large prospective study using QCT," J. Bone Mineral Res., vol. 23, no. 8, pp. 1326-1333, 2008. (Pubitemid 352040188)
48. M. Ito, N. Wakao, T. Hida, Y. Matsui, Y. Abe, K. Aoyagi, M. Uetani, and A. Harada, "Analysis of hip geometry by clinical CT for the assessment of hip fracture risk in elderly Japanese women," Bone, vol. 46, no. 2, pp. 453-457, 2010.
49. R. Zoroofi, Y. Sato, T. Sasama, T. Nishii, N. Sugano, K. Yonenobu, H. Yoshikawa, T. Ochi, and S. Tamura, "Automated segmentation of acetabulum and femoral head from 3-D CT images," IEEE Trans. Inf. Technol. Biomed., vol. 7, no. 4, pp. 329-343, Dec. 2003.
50. L. Humbert, T. Whitmarsh, M. De Craene, L. M. del Río Barquero, K. Fritscher, R. Schubert, F. Eckstein, T. Link, and A. F. Frangi, "3D reconstruction of both shape and bone mineral density distribution of the femur from DXA images," in Proc. 2010 IEEE Int. Conf. Biomed. Imag.: From Nano to Macro, 2010, pp. 456-459.
51. J. Haczynski and A. Jakimiuk, "Vertebral fractures: A hidden problem of osteoporosis," Med. Sci. Monitor, vol. 7, no. 5, pp. 1108-1117, 2001. (Pubitemid 32928638)
52. K. Fritscher, A. Grunerbl,M.Hanni,N. Suhm, C.Hengg, andR. Schubert, "Trabecular bone analysis in CT and X-ray images of the proximal femur for the assessment of local bone quality," IEEE Trans.Med. Imag., vol. 28, no. 10, pp. 1560-1575, Oct. 2009.