Abstract
Radiologists identify abnormal pathologies including fractures with a high level of accuracy. However in some cases the examining reader accuracy may show high miss rate while reading X-rays containing abnormalities such as multiple patellar fracture. Accurate diagnosis of fractures is vital to the effective management of patient injuries. As a result, detection of patellar fracture is an important orthopedics and radiologic problem. In this paper, attempt has been made to develop an algorithm which will identify global thresholding ranges for different edge detection operators e.g. Sobel, Prewitt, Canny, Laplacian of Gaussian for analysis of fractured patella, which will help the orthopedic surgeons for analyzing the fracture in a better form than conventional method of diagnosis which is subjective, time consuming and tedious. The processing algorithms are developed on MATLAB 7.6.0 (R2008a) programming platform.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chai, H.Y., Wee, L.K., Swee, T.T., Hussain, S.: Gray-Level Co-occurrence Matrix Bone Fracture Detection. Am. J. Applied Sci. 8, 26–32 (2011)
Pham, D.L., Xu, C., Prince, J.L.: Current Methods in Medical Image Segmentation. Annu. Rev. Biomed. Eng. 2, 315–337 (2000)
Neelgar, B.I., Benakop, P.G.: Analysis of Segmentation of Femur by Filtering Techniques. Ind. J. Sc. Tech. 1, 1–5 (2008)
Waugh, A., Grant, A.: Anatomy and Physiology in Health and Illness, 10th edn. Churchill Livingstone-Elsevier (2001)
Patella Fracture: Causes, Diagnosis and Treatment, http://www.joint-pain-expert.net/patella-fracture.html
Medscape Reference, http://emedicine.medscape.com/article/394270-overview
Mahendran, S.K., Baboo, S.S.: Enhanced Automatic X-ray Bone Image Segmentation using Wavelets and Morphological Operators. In: Int. Conf. on Information and Electronics Eng., pp. 125–129. IACSIT Press, Singapore (2011)
Chen, H.C., Wu, C.H., Lin, C.J., Liu, Y.H., Sun, Y.N.: Automated Segmentation for Patella from Lateral Knee X-ray Images. In: 31st Annu. Int. Conf. of the IEEE EMBS, pp. 3553–3556 (2009)
Meer, P., Georgescu, B.: Edge Detection with Embedded Confidence. IEEE Trans. on Pattern Analysis and Machine Intelligence 23, 1351–1365 (2001)
Nadernejad, E., Sharifzadeh, S., Hassanpour, H.: Edge Detection Techniques: Evaluation and Comparisons. Applied Mathematical Sciences 2, 1507–1520 (2008)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd edn. Prentice Hall (2001)
Moustafa, A.A., Alqadi, Z.A.: A Practical Approach of Selecting the Edge Detector Parameters to Achieve a Good Edge Map of the Gray Image. J. Comput. Sci. 5, 355–362 (2009)
Canny, J.: A Computational Approach to Edge Detection. IEEE Trans. on Pattern Analysis and Machine Intalligence 8, 679–714 (1986)
Sezgin, M., Sankur, B.: Survey Over Image Thresholding Techniques and Quantitative Performance Evaluation. J. Electronic Imaging 13, 146–165 (2004)
Tian, T.-P., Chen, Y., Leow, W.-K., Hsu, W., Howe, T.S., Png, M.A.: Computing Neck-Shaft Angle of Femur for X-Ray Fracture Detection. In: Petkov, N., Westenberg, M.A. (eds.) CAIP 2003. LNCS, vol. 2756, pp. 82–89. Springer, Heidelberg (2003)
Zahurul, S., Zahidul, S., Jidin, R.: An Adept Edge Detection Algorithm for Human Knee Osteoarthritis Images. In: Int. Conf. on Signal Acq. and Processing, pp. 375–379 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Datta, S., Chakraborty, M. (2011). Patellar Fracture Analysis Using Segmentation and Global Thresholding Techniques. In: Das, V.V., Thankachan, N. (eds) Computational Intelligence and Information Technology. CIIT 2011. Communications in Computer and Information Science, vol 250. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25734-6_27
Download citation
DOI: https://doi.org/10.1007/978-3-642-25734-6_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25733-9
Online ISBN: 978-3-642-25734-6
eBook Packages: Computer ScienceComputer Science (R0)