20 February 2018 A novel algorithm for osteoarthritis detection in Hough domain
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Abstract
Background subtraction of knee MRI images has been performed, followed by edge detection through canny edge detector. In order to avoid the discontinuities among edges, Daubechies-4 (Db-4) discrete wavelet transform (DWT) methodology is applied for the smoothening of edges identified through canny edge detector. The approximation coefficients of Db-4, having highest energy is selected to get rid of discontinuities in edges. Hough transform is then applied to find imperfect knee locations, as a function of distance (r) and angle (θ). The final outcome of the linear Hough transform is a two-dimensional array i.e., the accumulator space (r, θ) where one dimension of this matrix is the quantized angle θ and the other dimension is the quantized distance r. A novel algorithm has been suggested such that any deviation from the healthy knee bone structure for diseases like osteoarthritis can clearly be depicted on the accumulator space.
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Sabyasachi Mukhopadhyay, Nilanjan Poria, Rajanya Chakraborty, Sawon Pratiher, Sukanya Mukherjee, Prasanta K. Panigrahi, "A novel algorithm for osteoarthritis detection in Hough domain", Proc. SPIE 10506, Nanoscale Imaging, Sensing, and Actuation for Biomedical Applications XV, 105061E (20 February 2018); doi: 10.1117/12.2290326; https://doi.org/10.1117/12.2290326
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