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https://scholarbank.nus.edu.sg/handle/10635/39343
Title: | Computing neck-shaft angle of femur for X-ray fracture detection | Authors: | Tian, T.P. Chen, Y. Leow, W.K. Hsu, W. Howe, T.S. Png, M.A. |
Issue Date: | 2003 | Citation: | Tian, T.P.,Chen, Y.,Leow, W.K.,Hsu, W.,Howe, T.S.,Png, M.A. (2003). Computing neck-shaft angle of femur for X-ray fracture detection. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2756 : 82-89. ScholarBank@NUS Repository. | Abstract: | Worldwide, 30%-40% of women and 13% of men suffer from osteoporotic fractures of the bone, particularly the older people. Doctors in the hospitals need to manually inspect a large number of x-ray images to identify the fracture cases. Automated detection of fractures in x-ray images can help to lower the workload of doctors by screening out the easy cases, leaving a small number of difficult cases and the second confirmation to the doctors to examine more closely. To our best knowledge, such a system does not exist as yet. This paper describes a method of measuring the neck-shaft angle of the femur, which is one of the main diagnostic rules that doctors use to determine whether a fracture is present at the femur. Experimental tests performed on test images confirm that the method is accurate in measuring neck-shaft angle and detecting certain types of femur fractures. © Springer-Verlag Berlin Heidelberg 2003. | Source Title: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | URI: | http://scholarbank.nus.edu.sg/handle/10635/39343 | ISSN: | 03029743 |
Appears in Collections: | Staff Publications |
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