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Computerized Bone Age Assessment Using DCT and LDA

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4418))

Abstract

This paper presents a computerized bone age assessment method using discrete cosine transform (DCT) and Fisher’s linear discriminant analysis (FLD or LDA). Bone age assessment using a radiograph of the left hand is a common procedure in pediatric radiology. In the proposed method, DCT and LDA are applied to the epiphyseal regions segmented from a radiograph of the left hand. The extracted LDA coefficients are compared with features stored in the database, and then the bone age of the given radiograph is estimated. In experiments on 396 radiographs of the left hand collected at Hanyang University Medical Center, the proposed method shows an average error of 0.6 years and an accuracy of 89.71%.

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References

  1. Tanner, J.M., Whitehouse, R.H.: Assessment of Skeletal Maturity and Prediction of Adult Height (TW2 Method). Academic Press, London (1975)

    Google Scholar 

  2. Greulich, W.W., Pyle, S.I.: Radiographic Atlas of Skeletal Development of Hand Wrist, 2nd edn. Standford Univ. Press, Stanford (1971)

    Google Scholar 

  3. Miler, G.R., Levick, R.K., Kay, R.: Assessment of Bone Age: A Comparison of the Greulich and Pyle, and the Tanner and Whitehouse Methods. Clinical Radiology 37, 119–121 (1986)

    Article  Google Scholar 

  4. Pietka, E., et al.: Computer-Assisted Bone Age Assessment: Image Preprocessing and Epiphyseal/Metaphyseal ROI Extraction. IEEE Transactions on Medical Imaging 20(8), 715–729 (2001)

    Article  Google Scholar 

  5. Mahmoodi, S., et al.: Skeletal Growth Estimation Using Radiographic Image Processing and Analysis. IEEE Transaction on Information Technology in Biomedicine 4(4), 292–297 (2000)

    Article  Google Scholar 

  6. Mahmoodi, S., et al.: Bayesian Estimation of Growth Age Using Shape and Texture Descriptors. In: International Conference on Image Processing and its Applications, pp. 489–493 (1999)

    Google Scholar 

  7. Al-Taani, A.T., Ricketts, I.W., Cairns, A.Y.: Classification of Hand Bones for Bone Age Assessment. In: International Conference on Electronics, Circuits, and Systems, vol. 2, pp. 1088–1091 (1996)

    Google Scholar 

  8. Marques Da Silva, A.M., et al.: On Determining a Signature for Skeletal Maturity. In: Brazilian Symposium on Computer Graphics and Image Processing, pp. 246–251 (2001)

    Google Scholar 

  9. Tristan, A., Arribas, J.I.: A Radius and Ulna Skeletal Age Assessment System. In: IEEE Workshop on Machine Learning for Signal Processing, pp. 221–226. IEEE Computer Society Press, Los Alamitos (2005)

    Chapter  Google Scholar 

  10. Bocchi, L., et al.: An Artificial Neural Network Architecture for Skeletal Age Assessment. In: International Conference on Image Processing, vol. 1, pp. 1077–1080 (2003)

    Google Scholar 

  11. Pietka, E., et al.: Computer-Assisted Phalangeal Analysis in Skeletal Age Assessment. IEEE Transactions on Medical Imaging 10(4), 616–620 (1991)

    Article  Google Scholar 

  12. Pietka, E., et al.: Feature Extraction in Carpal-Bone Analysis. IEEE Transactions on Medical Imageing 12(1), 44–49 (1993)

    Article  Google Scholar 

  13. Mahmoodi, S., et al.: Automated Vision System for Skeletal Age Assessment Using Knowledge Based Techniques. In: International Conference on Image Processing and its Applications, vol. 2, pp. 809–813 (1997)

    Google Scholar 

  14. Chang, C.-H., et al.: A Fully Automatic Computerized Bone Age Assessment Procedure Based on Phalange Ossification Analysis. In: IPPR Conference on Computer Vision, Graphics and Image Processing, pp. 463–468 (2003)

    Google Scholar 

  15. Niemeijer, M., et al.: Assessing the Skeletal Age From a Hand Radiograph: Automating the Tanner-Whitehouse Method. In: SPIE Medical Imaging, vol. 5032, pp. 1197–1205 (2003)

    Google Scholar 

  16. Jang, S.-H., et al.: Automatic bone age estimation using eigen analysis of epiphyseal region. In: Asia pacific paediatric endocrine society, the 3rd biennial scientific meeting, p. 69 (2004)

    Google Scholar 

  17. Jang, S.-H.: Automatic bone age assessment system using radiographic image processing and pattern analysis technique. Ph.D. Thesis, Hanyang University (2005)

    Google Scholar 

  18. Lee, H.-J., Kim, H.-J., Kim, W.-Y.: Face Recognition using Component-Based DCT/LDA. In: International Workshop on Advanced Image Technology, pp. 25–30 (2005)

    Google Scholar 

  19. Martinez, A.M., Kak, A.C.: PCA versus LDA. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(2), 228–233 (2001)

    Article  Google Scholar 

  20. Kittler, J., Li, Y.P., Matas, J.: On Matching Scores for LDA-based Face Verification. In: The British Machine Vision Conference, pp. 42–51 (2000)

    Google Scholar 

  21. Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice Hall, Englewood Cliffs (2002)

    Google Scholar 

  22. Belhumeur, V., Hespanha, J., Kriegman, D.: Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(7), 711–720 (1992)

    Article  Google Scholar 

  23. http://hmct.hanyang.ac.kr/

  24. Duda, R., Hart, P.: Pattern classification and scene analysis. Wiley, New York (1973)

    MATH  Google Scholar 

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André Gagalowicz Wilfried Philips

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© 2007 Springer Berlin Heidelberg

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Kim, HJ., Kim, WY. (2007). Computerized Bone Age Assessment Using DCT and LDA. In: Gagalowicz, A., Philips, W. (eds) Computer Vision/Computer Graphics Collaboration Techniques. MIRAGE 2007. Lecture Notes in Computer Science, vol 4418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71457-6_40

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  • DOI: https://doi.org/10.1007/978-3-540-71457-6_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71456-9

  • Online ISBN: 978-3-540-71457-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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