Abstract
Medical imaging has advanced at a tremendous rate since x-rays were discovered in 1895. Today, x-ray machines produce extremely high-quality images for radiologists to interpret. However, the methods of interpretation have only recently begun to be augmented by advances in computer technology. Computer aided diagnosis (CAD) systems that guide healthcare professionals in making the correct diagnosis are slowly becoming more prevalent throughout the medical field. Detection of long-bone fractures is an important orthopaedic and radiologic problem, and it is proposed that a novel CAD system could help reduce the number of fractures missed during x-ray diagnosis. A number of image processing software algorithms useful for assisting the fracture detection process are described, and their accuracy evaluated on a database of fracture images from trauma patients. Incorporating these methods will further expand the capabilities of today’s CAD systems, and result in more accurate diagnosis of fractures and a reduction of the fracture miss rate.
Chapter PDF
Similar content being viewed by others
References
Chipchase, L.S., McCaul, K., Hearn, T.C.: Hip fracture rates in South Australia: Into the next century. Australian and New Zealand Journal of Surgery 70(2), 117–119 (2000)
Sanders, K.M., Nicholson, G.C., Ugoni, A.M., Pasco, J.A., Seeman, E., Kotowicz, M.A.: Health burden of hip and other fractures in Australia beyond 2000. Projections based on the Geelong Osteoporosis Study. Medical Journal of Australia 170(10), 467–470 (1999)
Berlin, L.: Reporting the missed radiologic diagnosis: Medicolegal and ethical considerations. Radiology 192(1), 183–187 (1994)
Marr, D.: Vision: A computational investigation into the Human Representation and Processing of Visual Information. W. H. Freeman and Company, New York (1982)
Alvarez, L., Lions, P.L., Morel, J.M.: Image selective smoothing and edge detection by nonlinear diffusion. SIAM Journal of Numerical Analysis 29(3), 845–866 (1992)
Atiquzzaman, M.: Multiresolution Hough transform - An efficient method of de- tecting pattern in images. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(11), 1090–1095 (1992)
Skingley, J., Rye, A.: The Hough transform applied to SAR images for thin line detection. Pattern Recognition Letters 6(1), 61–67 (1987)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Donnelley, M., Knowles, G., Hearn, T. (2008). A CAD System for Long-Bone Segmentation and Fracture Detection. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds) Image and Signal Processing. ICISP 2008. Lecture Notes in Computer Science, vol 5099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69905-7_18
Download citation
DOI: https://doi.org/10.1007/978-3-540-69905-7_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69904-0
Online ISBN: 978-3-540-69905-7
eBook Packages: Computer ScienceComputer Science (R0)