Abstract
We describe a fully-automated system for analysing X-rays of the wrist to identify possible fractures. Fractures of the distal radius in the wrist are estimated to be about 18% of the fractures seen in adults and 25% of those seen in children. Unfortunately such fractures are amongst the most frequently missed by doctors in Emergency Departments (EDs). A system which can identify suspicious areas could reduce the number of misdiagnoses. We automatically locate the outline of the radius in both posteroanterior (PA) and lateral (LAT) radiographs, then use shape and texture features to classify abnormalities. We show for the first time that fractures can be better identified in the lateral view, and that combining information from both views leads to an overall improvement in performance.
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
Bayram, F., Çakirolu, M.: DIFFRACT: diaphyseal femur fracture classifier system. Biocybern. Biomed. Eng. 36(1), 157–171 (2016)
Cao, Y., Wang, H., Moradi, M., Prasanna, P., Syeda-Mahmood, T.F.: Fracture detection in x-ray images through stacked random forests feature fusion. In: International Symposium on Biomedical Imaging (ISBI 2015), pp. 801–805, April 2015
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. IEEE Trans. Pattern Anal. Mach. Intell. 23(6), 681–685 (2001)
Court-Brown, C.M., Caesar, B.: Epidemiology of adult fractures: a review. Injury 37, 691–697 (2006)
Ebsim, R., Naqvi, J., Cootes, T.: Detection of wrist fractures in X-Ray images. In: Shekhar, R., et al. (eds.) CLIP 2016. LNCS, vol. 9958, pp. 1–8. Springer, Cham (2016). doi:10.1007/978-3-319-46472-5_1
Goldfarb, C.A., Yin, Y., Gilula, L.A., Fisher, A.J., Boyer, M.I.: Wrist fractures: what the clinician wants to know. Radiology 219, 11–28 (2001)
Guly, H.R.: Injuries initially misdiagnosed as sprained wrist (beware the sprained wrist). Emergency Med. J. (EMJ) 19, 41 (2002)
Lee, C., Bleetman, A.: Commonly missed injuries in the accident and emergency department. Trauma 6, 41–51 (2004)
Lim, S.E., Xing, Y., Chen, Y., Leow, W.K., Howe, T.S., Png, M.A.: Detection of femur and radius fractures in x-ray images. In: Proceedings of 2nd International Conference on Advances in Medical Signal and Information Processing, vol. 1, pp. 249–256 (2004)
Lindner, C., Bromiley, P.A., Ionita, M.C., Cootes, T.: Robust and accurate shape model matching using random forest regression-voting. IEEE Trans. Pattern Anal. Mach. Intell. 37(9), 1862–1874 (2015)
Lindner, C., Thiagarajah, S., Wilkinson, J.M., Consortium, T., Wallis, G.A., Cootes, T.F.: Fully automatic segmentation of the proximal femur using random forest regression voting. Med. Image Anal. 32(8), 1462–1472 (2013)
Lum, V.L.F., Leow, W.K., Chen, Y., Howe, T.S., Png, M.A.: Combining classifiers for bone fracture detection in X-ray images, vol. 1, pp. I-1149–1152 (2005)
McLauchlan, C.A., Jones, K., Guly, H.R.: Interpretation of trauma radiographs by junior doctors in accident and emergency departments: a cause for concern? J. Accid. Emerg. Med. 14(5), 295–298 (1997)
Petinaux, B., Bhat, R., Boniface, K., Aristizabal, J.: Accuracy of radiographic readings in the emergency department. Am. J. Emerg. Med. 29, 18–25 (2011)
Porrino, J.A., Maloney, E., Scherer, K., Mulcahy, H., Ha, A.S., Allan, C.: Fracture of the distal radius: epidemiology and premanagement radiographic characterization. Am. J. Roentgenol. (AJR) 203, 551–559 (2014)
Roberts, M.G., Oh, T., Pacheco, E.M.B., Mohankumar, R., Cootes, T.F., Adams, J.E.: Semi-automatic determination of detailed vertebral shape from lumbar radiographs using active appearance models. Osteoporos. Int. 23(2), 655–664 (2012)
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). doi:10.1007/978-3-540-45179-2_11
Wei, C.-J., Tsai, W.-C., Tiu, C.-M., Wu, H.-T., Chiou, H.-J., Chang, C.-Y.: Systematic analysis of missed extremity fractures in emergency radiology. Acta Radiologica 47, 710 (2006)
Jia, Y.: Active contour model with shape constraints for bone fracture detection. In: International Conference on Computer Graphics, Imaging and Visualisation (CGIV 2006), vol. 3, pp. 90–95 (2006)
Yap, D.W.H., Chen, Y., Leow, W.K., Howe, T.S., Png, M.A.: Detecting femur fractures by texture analysis of trabeculae. In: Proceedings - International Conference on Pattern Recognition vol. 3, pp. 730–733 (2004)
Acknowledgment
The research leading to these results has received funding from Libyan Ministry of Higher Education and Research. The authors would like to thank Dr Jonathan Harris, Dr Matthew Davenport, and Dr Martin Smith for their collaboration to set up the project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Ebsim, R., Naqvi, J., Cootes, T. (2017). Fully Automatic Detection of Distal Radius Fractures from Posteroanterior and Lateral Radiographs. In: Cardoso, M., et al. Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures. CARE CLIP 2017 2017. Lecture Notes in Computer Science(), vol 10550. Springer, Cham. https://doi.org/10.1007/978-3-319-67543-5_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-67543-5_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67542-8
Online ISBN: 978-3-319-67543-5
eBook Packages: Computer ScienceComputer Science (R0)