Abstract
For many orthopedics, neurosurgeon and radiologists, the extraction of the spinal column and detection of each vertebra is essential. It helps in the identification of vertebral abnormalities like cervical trauma, osteoporosis, spinal ruptures etc. Computer aided diagnostic systems for the localization and extraction of vertebra from X-ray images are important to perform mass screening. It is a challenging task to be performed due to low contrast imaging and noise present in X-ray images. In this paper, we present a technique for automatic detection and extraction of vertebrae area. The proposed technique takes a radiograph as input and detects the location of cervical vertebrae \((C_3\)–\(C_7)\) using generalized Hough Transform and Fuzzy C-mean clustering. In order to obtain the region for each vertebra, distances between two consecutive vertebrae are calculated and their centroids are found. Then perpendicular separating lines are found on these centroids by applying affine transformation on the line passing through centroid and joining two vertebra. After rotation, these lines are combined to obtain 5 regions for each vertebra \((C_3\)–\(C_7)\). The proposed method has been tested using 50 radiographs from which 250 vertebrae are detected. The dataset ‘NHANESII’ used is publically available at National Library of Medicine (NLM). The results show the validity of presented technique.
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Mehmood, A., Akram, M.U., Akhtar, M., Usman, A. (2017). Separation of Vertebrae Regions from Cervical Radiographs Using Inter-Vertebra Distance and Orientation. In: Abraham, A., Haqiq, A., Alimi, A., Mezzour, G., Rokbani, N., Muda, A. (eds) Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016). HIS 2016. Advances in Intelligent Systems and Computing, vol 552. Springer, Cham. https://doi.org/10.1007/978-3-319-52941-7_4
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