Abstract
Total hip replacement is the accepted treatment procedure of the end stage degeneration of the hip joint. Instability of the prosthesis might be recognized on the radiographic images as area of bone radio - lucency adjacent to the prosthesis pin. However, the very important issue of radiological recognition of periprosthetic lucent areas reflecting the lysis remains a challenge. Small dimensions and fuzzy borders of the lytic areas makes them difficult regions to recognize. Additional factors as high BMI of the patients and/or radiograms taken through a mattress can make the evaluation even more difficult, while small lucent areas might be additionally blurred and of very low contrast. The paper presents a new approach for quantitative recognition of preprothetic lytic areas. We have proposed a multistep algorithm utilizing Statistical Dominance Transform for detection of lytic areas on digital radiograms. Preliminary results are quite promising. It was demonstrated that location and shape of the detected lytic region is in good agreement with assessment by radiologists.
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
Similar content being viewed by others
References
Bauer, T.W., Schils, J.: The pathology of total joint arthroplasty. Skelet. Radiol. 28(9), 483–497 (1999). https://doi.org/10.1007/s002560050552
Bielecka, M., Korkosz, M.: Generalized shape language application to detection of a specific type of bone erosion in X-ray images. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2016. LNCS (LNAI), vol. 9692, pp. 531–540. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39378-0_45
Bogusiak, K., Kocinski, M., Lutkowski, A., Materka, A., Arkuszewski, P.: Changes in measurements of segner-hasund analysis in patients with mandibular prognathism after orthognathic surgery. Dent. Med. Probl 53(1), 13–21 (2016)
Chrzanowski, L., Drozdz, J., Strzelecki, M., Krzeminska-Pakula, M., Jedrzejewski, K., Kasprzak, J.: Application of neural networks for the analysis of histological and ultrasonic aortic wall appearance-an invitro tissue characterization study. Ultrasound Med. Biol. 34(2008), 103–113 (2008)
Claus, A.M., Totterman, S.M., Sychterz, C.J., Tamez-Peña, J.G., Looney, R.J., Engh Sr., C.A.: Computed tomography to assess pelvic lysis after total hip replacement. Clin. Orthop. Relat. Res. 422, 167–174 (2004)
Kropidłowski, K., Kociołek, M., Strzelecki, M., Czubiński, D.: Model based approach for melanoma segmentation. In: Chmielewski, L.J., Kozera, R., Shin, B.-S., Wojciechowski, K. (eds.) ICCVG 2014. LNCS, vol. 8671, pp. 347–355. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11331-9_42
Larroza, A., Bodí, V., Moratal, D.: Texture analysis in magnetic resonance imaging: Review and considerations for future applications. In: Assessment of Cellular and Organ Function and Dysfunction Using Direct and Derived MRI Methodologies. InTech (2016)
Materka, A., Strzelecki, M.: On the importance of MRI nonuniformity correction for texture analysis. In: Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA) 2013, pp. 118–123. IEEE (2013)
Mjöberg, B.: The theory of early loosening of hip prostheses. Orthopedics 20(12), 1169–1175 (1997)
Piórkowski, A.: A statistical dominance algorithm for edge detection and segmentation of medical images. In: Piȩtka, E., Badura, P., Kawa, J., Wieclawek, W. (eds.) Information Technologies in Medicine. AISC, vol. 471, pp. 3–14. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39796-2_1
Thevenot, J., et al.: Trabecular homogeneity index derived from plain radiograph to evaluate bone quality. J. Bone Mineral Res. 28(12), 2584–2591 (2013)
Wilkie, J.R., Giger, M.L., Engh, C.A., Hopper, R.H., Martell, J.M.: Radiographic texture analysis in the characterization of trabecular patterns in periprosthetic osteolysis. Acad. Radiol. 15(2), 176–185 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Kociołek, M., Piórkowski, A., Obuchowicz, R., Kamiński, P., Strzelecki, M. (2018). Lytic Region Recognition in Hip Radiograms by Means of Statistical Dominance Transform. In: Chmielewski, L., Kozera, R., Orłowski, A., Wojciechowski, K., Bruckstein, A., Petkov, N. (eds) Computer Vision and Graphics. ICCVG 2018. Lecture Notes in Computer Science(), vol 11114. Springer, Cham. https://doi.org/10.1007/978-3-030-00692-1_31
Download citation
DOI: https://doi.org/10.1007/978-3-030-00692-1_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00691-4
Online ISBN: 978-3-030-00692-1
eBook Packages: Computer ScienceComputer Science (R0)