Active Contour Based Developmental Hip Dysplasia Diagnosis with Graf Method

Authors

  • Kerim Kürşat ÇEVIK
  • Hasan Erdinç KOÇER

DOI:

Keywords:

Developmental Hip Dysplasia, Ultrasound, Active Contour Model, Image Processing

Abstract

In this article, a study was carried on ultrasound (US) images for the automatic diagnosis of the disease of the developmental hip dysplasia (DDH). It was aimed with this study at minimizing the errors of the experts in DDH diagnosis. As a first step in the study; commonly known as the images and reduce noise in the US image, image filter are applied to improve the quality. In the second stage; by using Active Contour Model method it was determined acetabular roof and labrum areas. In the third stage; alpha and beta angles that is necessary to be applied Graf method and used DDH diagnosis are determined by using various morphological image algorithms on the image. In the last stage, the classification of Graf method was made and the performance of the system was measured by comparing expert data and the results. According to type conditions of Graf method, in the images of 40 out of 50 it was found the same due to software which was designed with expert data. In the remaining 10 images, expert result and program result are rather close especially for alpha angle. As a result, the success rate of the system for the 50 image is 80%. When considered the parameters such as the difficulty of physical examination of DDH diagnosis, decreasing quality of life in the people suffered from this disease, limb shortening, limping, functional disability, treatment costs, based on expert data and relativism of applying of Graf method on US images, the importance of DDH diagnosis system supported computer is seen.

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References

Doğruel, H., et al., Türkiye’de gelişimsel kalça displazisi sıklığının ve tarama programlarının değerlendirilmesi. Türkiye Klinikleri J Med Sci, 2008. 28: p. 357-360.

Tosun, H.B., Gelişimsel kalça displazisi taraması için yapılan kalça ultrasonografisi sonuçlarının değerlendirilmesi, in Tıp Fakültesi Ortopedi ve Travmatoloji Anabilim Dalı. 2010, Fırat Üniversitesi: Elazığ, Türkiye. p. 100.

Song, K. and A. Lapinsky, Determination of hip position in the Pavlik harness. Journal of Pediatric Orthopaedics, 2000. 20(3): p. 317-319.

Rosendahl, K., T. Markestad, and R. Lie, Ultrasound screening for developmental dysplasia of the hip in the neonate: the effect on treatment rate and prevalence of late cases. Pediatrics, 1994. 94(1): p. 47-52.

Herring, J.A., Tachdjian’s Pediatric Orthopaedics: From the Texas Scottish Rite Hospital for Children. Vol. 3. 2003, Philadelphia, U.S.A.: Elsevier-Saunders. 2144.

Tuncay, I.C., et al., Is prematurity important in ultrasonographic hip typing? Journal of Pediatric Orthopaedics B, 2005. 14: p. 168–171.

Harcke, H.T., Imaging methods used for children with hip dysplasia. Clin Orthop Relat Res., 2005. 434: p. 71-77.

Graf, R., Hip sonography: diagnosis and management of infant hip dysplasia. 2006: Springer Science & Business Media.

Şaşmaz, H.H., Gelişimsel kalça displazisi tanısında sonografik tarama tekniklerinin karşılaştırılması, in Tıp Fakültesi Radyoloji Anabilim Dalı. 2011, Gaziantep Üniversitesi: Gaziantep, Türkiye. p. 113.

Kapıcıoğlu, S., et al., 0-6 ay arası GKD ve PEV tanı ve tedavisi uygulamalı kursu kitapçığı. Vol. 4. 2006, Konya: TOTBİD.

Overhoff, H., et al., Computer-based determination of the newborn’s femoral head coverage using three-dimensional ultrasound scans, in Medical Image Computing and Computer-Assisted Interventation — MICCAI’98, W. Wells, A. Colchester, and S. Delp, Editors. 1998, Springer Berlin Heidelberg. p. 1024-1031.

Luis-García, R. and C. Alberola-López. Hip joint segmentation from 2D ultrasound data based on dynamic shape priors. in Proceedings of the 4th WSEAS international conference on Electronics, control and signal processing. 2005. World Scientific and Engineering Academy and Society (WSEAS).

Luis-Garcia, R. and C. Alberola-Lopez. Parametric 3D hip joint segmentation for the diagnosis of developmental dysplasia. in Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE. 2006.

Luis-Garcia, R., S. Aja-Fernandez, and R. Cardenes-Almeida, Analysis of ultrasound images based on local statistics. Application to the diagnosis of developmental dysplasia of the hip, in 2007 IEEE Ultrasonics Symposium. 2007. p. 2531-2534.

Chen, H.-Y., et al. Application of segmentation and measurement in the treatment of developmental dysplasia of the hip. in Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on. 2007.

Çevik, K.K., H.E. Koçer, and Ş. Andaç, Segmentation of the Ilium and Femur Regions from Ultrasound Images for Diagnosis of Developmental Dysplasia of the Hip J. Med. Imaging Health Inf., 2016. 6(2): p. 449-457.

Hafizah, W.M. and E. Supriyanto, Comparative evaluation of ultrasound kidney image enhancement techniques. International Journal of Computer Applications, 2011. 21(7): p. 15-19.

Chan, T.F., B.Y. Sandberg, and L.A. Vese, Active contours without edges for vector-valued images. Journal of Visual Communication and Image Representation, 2000. 11(2): p. 130-141.

Chan, T.F. and L.A. Vese, Active contours without edges. Image Processing, IEEE Transactions on, 2001. 10(2): p. 266-277.

Chenyang, X. and J.L. Prince, Snakes, shapes, and gradient vector flow. Image Processing, IEEE Transactions on, 1998. 7(3): p. 359-369.

Osher, S. and R. Fedkiw, Level set methods and dynamic implicit surfaces. Vol. 153. 2006, New York: Springer Science & Business Media. 280.

Sapiro, G., Geometric partial differential equations and image analysis. 2006, New York: Cambridge university press. 386.

Chesnaud, C., P. Réfrégier, and W. Boulet, Statistical region snake-based segmentation adapted to different physical noise models. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1999. 21(11): p. 1145-1157.

Chunming, L., et al. Level set evolution without re-initialization: a new variational formulation. in Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on. 2005.

Suri, J.S., et al., Shape recovery algorithms using level sets in 2-D/3-D medical imagery: a state-of-the-art review. Information Technology in Biomedicine, IEEE Transactions on, 2002. 6(1): p. 8-28.

Malladi, R., J. Sethian, and B.C. Vemuri, Shape modeling with front propagation: A level set approach. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1995. 17(2): p. 158-175.

Osher, S. and J.A. Sethian, Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations. Journal of Computational Physics, 1988. 79(1): p. 12-49.

Özmen, N., Image segmentation and smoothing via partial differential equations, in The Graduate School Of Applied Mathematics. 2009, Middle East Technical University: Ankara. p. 102.

Tunali, I. and E. Kilic. Mass segmantation on mammograms using active contours. in Signal Processing and Communications Applications Conference (SIU), 2013 21st. 2013.

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Published

01-12-2016

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Section

Research Articles

How to Cite

[1]
“Active Contour Based Developmental Hip Dysplasia Diagnosis with Graf Method”, J. Appl. Methods Electron. Comput., pp. 230–235, Dec. 2016, Accessed: Nov. 25, 2024. [Online]. Available: https://ijamec.org/index.php/ijamec/article/view/186

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