Abstract
In this paper, a method of parameterisation of a proximal femur model is presented. The created model retains all the anatomical and morphological features of a realistic model. The parametric model of the femur, the so-called master model, is defined by establishing a relation between appropriate femoral regions which extend along the parametrically described axis of the femur. An initial 3D model of the femur is segmented from the CT image and further parameterized to a master model with the potential for customization, i.e. for adaptation to patient-specific values using X-ray images, still maintaining precise anatomical consistency. The first step towards the femur customization is the contour extraction of different types of tissues represented in X-ray images. As medical images can be blurry, image processing was carried out and a Canny edge detector operator was applied. The numerical values of the parameters were determined by manual measuring of defined regions on an X-ray image. The variability testing was performed on 12 femurs. The proposed model can greatly contribute to preoperative planning, implant selection, as well as to the overall shortening of intervention time.
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Abbreviations
- CT:
-
computer tomography
- RTG:
-
radiographic image
- S j(x):
-
spline function on the interval [xi, xi+1], i=0, 1, 2, …, n
- Aa, HAa :
-
coefficient matrix
- ai, bi, ci, di :
-
coefficients
- x :
-
knot position
- ACD:
-
neck angle (degrees)
- A:
-
femoral head diameter (mm)
- D, G, E, F:
-
width of the metaphyseal femur (mm)
- B:
-
intramedullary diameter (mm)
- CP1, CP2, CP3:
-
control parameters (mm)
- HVF, HNF :
-
high, low pass filter normalized transfer function
- u, v:
-
directions
References
Bagci, E., “Reverse Engineering Applications for Recovery of Broken or Worn Parts and Re-Manufacturing: Three Case Studies,” Advances in Engineering Software, Vol. 40, No. 6, pp. 407–418, 2009.
Hicks, J. L., Uchida, T. K., Seth, A., Rajagopal, A., and Delp, S. L., “Is my Model Good Enough? Best Practices for Verification and Validation of Musculoskeletal Models and Simulations of Movement,” Journal of Biomechanical Engineering, Vol. 137, No. 2, Paper No. 020905, 2015.
Galibarov, P., Prendergast, P., and Lennon, A., “A Method to Reconstruct Patient-Specific Proximal Femur Surface Models from Planar Pre-Operative Radiographs,” Medical Engineering and Physics, Vol. 32, No. 10, pp. 1180–1188, 2010.
Illés, T. and Somoskeöy, S., “The EOS™ Imaging System and Its Uses in Daily Orthopaedic Practice,” International Orthopaedics, Vol. 36, No. 7, pp. 1325–1331, 2012.
Vartziotis, D., Poulis, A., Faessler, V., Vartziotis, C., and Kolios, C., “Integrated Digital Engineering Methodology for Virtual Orthopedics Surgery Planning,” Proc. of the International Special Topies Conference on Information Technology in Biomedicine, 2006.
Chen, X., He, K., Chen, Z., and Wang, L., “A Parametric Approach to Construct Femur Models and their Fixation Plates,” Biotechnology & Biotechnological Equipment, Vol. 30, No. 3, pp. 529–537, 2016.
Matthews, F., Messmer, P., Raikov, V., Wanner, G. A., Jacob, A. L., et al., “Patient-Specific Three-Dimensional Composite Bone Models for Teaching and Operation Planning,” Journal of Digital Imaging, Vol. 22, No. 5, pp. 473–482, 2009.
Liu, B., Jia, X., Huang, Z., and Li, H., “An Improved System for 3D Individualized Modeling of the Artificial Femoral Head,” The Visual Computer, Vol. 29, No. 12, pp. 1259–1267, 2013.
Majstorovic, V., Trajanovic, M., Vitkovic, N., and Stojkovic, M., “Reverse Engineering of Human Bones by Using Method of Anatomical Features,” CIRP Annals-Manufacturing Technology, Vol. 62, No. 1, pp. 167–170, 2013.
Aghili, A. L., Goudarzi, A. M., Paknahad, A., Imani, M., and Mehrizi, A. A., “Finite Element Analysis of Human Femur by Reverse Engineering Modeling Method,” Indian Journal of Science and Technology, Vol. 8, No. 13, 2015. (DOI: 10.17485/ijst/2015/v8i13/47884)
Vitkovic, N., Trajanovic, M., Milovanovic, J., Korunovic, N., Arsic, S., and Ilic, D., “The Geometrical Models of the Human Femur and Its Usage in Application for Preoperative Planning in Orthopedics,” Proc. of the 1st International Conference on Internet Society Technology and Management-ICIST, 2011.
Chaibi, Y., Cresson, T., Aubert, B., Hausselle, J., Neyret, P., et al., “Fast 3D Reconstruction of the Lower Limb Using a Parametric Model and Statistical Inferences and Clinical Measurements Calculation from Biplanar X-rays,” Computer Methods in Biomechanics and Biomedical Engineering, Vol. 15, No. 5, pp. 457–466, 2012.
Stojkovic, M., Milovanovic, J., Vitkovic, N., Trajanovic, M., Arsic, S., and Mitkovic, M., “Analysis of Femoral Trochanters Morphology Based on Geometrical Model,” Journal of Scientific and Industrial Research, Vol. 71, No. 3, pp. 210–216, 2012.
Le Bras, A., Laporte, S., Bousson, V., Mitton, D., De Guise, J. A., et al., “3D Reconstruction of the Proximal Femur with Low-Dose Digital Stereoradiography,” Computer Aided Surgery, Vol. 9, No. 3, pp. 51–57, 2004.
Materialise, “Mimics Student Edition Course Book,” https://www.researchgate.net/profile/Yousof_Mohandes2/post/can_anyone_suggest_me_any_appropriate_resources_for_Learning_MIMICS_and_3Matic/attachment/59d635f579197b80779936d2/AS:386294329954307@1469111153848/download/Mimics+Student+Edition+Course+Book.pdf (Accessed 5 APR 2017)
Kia, R., Baboli, A., Javadian, N., Tavakkoli-Moghaddam, R., Kazemi, M., and Khorrami, J., “Solving a Group Layout Design Model of a Dynamic Cellular Manufacturing System with Alternative Process Routings, Lot Splitting and Flexible Reconfiguration by Simulated Annealing,” Computers & Operations Research, Vol. 39, No. 11, pp. 2642–2658, 2012.
Ferrer Arnau, L. J., Reig Bolano, R., Marti Puig, P., Manjabacas, A., and Parisi Baradad, V., “Efficient Cubic Spline Interpolation Implemented with FIR Filters,” International Journal of Computer Information Systems and Industrial Management Applications, Vol. 5, pp. 98–105, 2012.
Abbas, M., Majid, A. A., and Ali, J., “Positivity-Preserving C2 Rational Cubic Spline Interpolation,” ScienceAsia, Vol. 39, No. 2, pp. 208–213, 2013.
Noble, P. C., Alexander, J. W., Lindahl, L. J., Yew, D. T., Granberry, W. M., and Tullos, H. S., “The Anatomic Basis of Femoral Component Design,” Clinical Orthopaedics and Related Research, Vol., No. 235, pp. 148–165, 1988.
Roy, S. and Bandyopadhyay, S. K., “Detection and Quantification of Brain Tumor from MRI of Brain and It’s Symmetric Analysis,” International Journal of Information and Communication Technology Research, Vol. 2, No. 6, pp. 477–483, 2012.
Swaminathan, R. and Meyyappan, T., “Digital Image Filtering in Transform Domain Using MATLAB,” International Journal of Computer Applications, Vol. 158, No. 2, pp. 27–30, 2017.
Shubhangi, D., Raghavendra, S., and Hiremath, P., “Edge Detection of Femur Bones in X-ray Images -A Comparative Study of Edge Detectors,” International Journal of Computer Applications, Vol. 42, No. 2, pp. 975–8887, 2012.
Al-Ayyoub, M. and Al-Zghool, D., “Determining the Type of Long Bone Fractures in X-ray Images,” WSEAS Transactions on Information Science and Applications, Vol. 10, No. 8, pp. 261–270, 2013.
Heo, P., Gu, G. M., Lee, S.-J., Rhee, K., and Kim, J., “Current Hand Exoskeleton Technologies for Rehabilitation and Assistive Engineering,” International Journal of Precision Engineering and Manufacturing, Vol. 13, No. 5, pp. 807–824, 2012.
Tarnita, D., Boborelu, C., Popa, D., Tarnita, C., and Rusu, L., “The Three-Dimensional Modeling of the Complex Virtual Human Elbow Joint,” Romanian Journal of Morphology and Embryology, Vol. 51, No. 3, pp. 489–495, 2010.
Lee, J.-N., Luo, C.-W., Chen, H.-S., Kung, H.-K., and Tsai, Y.-C., “Developing the Custom-Made Femoral Component of Knee Prosthesis Using CAD/CAM,” Life Science Journal, Vol. 10, No. 2, pp. 259–264, 2013.
Yoo, D.-J., “Rapid Surface Reconstruction from a Point Cloud Using the Least-Squares Projection,” International Journal of Precision Engineering and Manufacturing, Vol. 11, No. 2, pp. 273–283, 2010.
Wang, M., “Optimal Selection System of Internal Fixation Methods for Femoral Neck Fracture,” Journal of Software, Vol. 9, No. 11, pp. 2911–2917, 2014.
Chanda, S., Gupta, S., and Pratihar, D. K., “A Combined Neural Network and Genetic Algorithm Based Approach for Optimally Designed Femoral Implant Having Improved Primary Stability,” Applied Soft Computing, Vol. 38, pp. 296–307, 2016.
Boussaid, H., Kadoury, S., Kokkinos, I., Lazennec, J.-Y., Zheng, G., and Paragios, N., “3D Model-Based Reconstruction of the Proximal Femur from Low-Dose Biplanar X-ray Images,” Proc. of the 22nd British Machine Vision Conference-BMVC 2011, pp. 1–10, 2011.
Stolojescu-CriSan, C. and Holban, S., “A Comparison of X-ray Image Segmentation Techniques,” Advances in Electrical and Computer Engineering, Vol. 13, No. 3, pp. 85–92, 2013.
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Savic, S.P., Ristic, B., Jovanovic, Z. et al. Parametric Model Variability of the Proximal Femoral Sculptural Shape. Int. J. Precis. Eng. Manuf. 19, 1047–1054 (2018). https://doi.org/10.1007/s12541-018-0124-x
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DOI: https://doi.org/10.1007/s12541-018-0124-x