Abstract
In this paper we present a Hough Transform-based method for the detection of the spinal district in X-ray Computed Tomography (CT) images in order to build binary masks that can be applied to functional images to infer information on the metabolic activity of the spinal marrow. This kind of information may be of particular interest for the study of the spinal marrow physiology in both health and disease.
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Hough, P.V.C.: Method and Means for Recognizing Complex Patterns. U.S. Patent 3069654 (1962)
Duda, R.O., Hart, P.E.: Use of the Hough transformation to detect lines and curves in pictures. Commun. ACM 15(1), 11–15 (1972)
Ballard, D.H.: Generalizing the Hough transform to detect arbitrary shapes. Pattern Recog. 11(2), 111–122 (1981)
Beltrametti, M.C., Massone, A.M., Piana, M.: Hough transform of special classes of curves. SIAM J. Imaging Sci. 6, 391–312 (2013)
Massone, A.M., Perasso, A., Campi, C., Beltrametti, M.C.: Profile detection in medical and astronomical images by means of the Hough transform of special classes of curves. J. Math. Imaging Vis. 51(2), 296–310 (2015)
Cistaro, A., et al.: Brain hypermetabolism in amyotrophic lateral sclerosis: a FDG PET study in ALS of spinal and bulbar onset. Eur. J. Nucl. Med. Mol. Imaging 39, 251–259 (2012)
Hickman, S.J., et al.: Application of a B-spline Active Surface Technique to the Measurement of Cervical Cord Volume in Multiple Sclerosis From Three-Dimensional MR Images. J. Magn. Reson. Imaging 18, 368–371 (2003)
Horsfield, M.A., et al.: Rapid semi-automated segmentation of the spinal cord from magnetic resonance images: Application in multiple sclerosis. NeuroImage 50, 446–455 (2010)
Archip, N., et al.: A Knowledge-Based Approach to Automatic Detection of the Spinal Cord in CT Images. IEEE Trans. Med. Imag. 21(12), 1504–1516 (2002)
Canny, J.F.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. PAMI 8(6) 679–698 (1986)
Rosset, A., Spadola, L., Ratib, O.: OsiriX: an open-source software for navigating in multidimensional DICOM images. J. Dig. Imag. 17(3), 205–216 (2004)
Aramini, R., Brignone, M., Coyle, J., Piana, M.: Postprocessing of the linear sampling method by means of deformable models. SIAM J. Sci. Comput. 30(5), 2613–2634 (2008)
The MathWorks, Inc. http://www.mathworks.com/help/curvefit/cftool.html (accessed May 31, 2015)
Ricca, G., Beltrametti, M.C., Massone, A.M.: Piecewise recognition of bone skeleton profiles via an iterative Hough transform approach without re-voting. In: Ourselin, S., Styner, M.A. (eds.) Proc. of SPIE Medical Imaging 2015: Image Processing, vol. 9413, p. 94132M
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Perasso, A., Campi, C., Massone, A.M., Beltrametti, M.C. (2015). Spinal Canal and Spinal Marrow Segmentation by Means of the Hough Transform of Special Classes of Curves. In: Murino, V., Puppo, E. (eds) Image Analysis and Processing — ICIAP 2015. ICIAP 2015. Lecture Notes in Computer Science(), vol 9279. Springer, Cham. https://doi.org/10.1007/978-3-319-23231-7_53
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DOI: https://doi.org/10.1007/978-3-319-23231-7_53
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