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Ethnographic Analysis Essay

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for vertebrae detection and segmentation acquired using different imaging modalities like X-Ray, CT and MRI. Various methods of vertebrae segmentation in 2-D and 3-D were analyzed and studied carefully. Among the various methods, region growing algorithm fails to segmented vertebrae because change intensity caused due to noise artifacts significantly affect segmentation. Watershed and morphological operation based approaches provide unclear boundary if the seed point is not properly identified. The statistical shape model approaches to segment vertebrae estimate the expectations about the shape of an object of interest from series of known images from the training set. But most of these approaches are sensitive to variations of pose parameters. …show more content…

b represents the bias field that indicates the intensity inhomogeneity. The bias field is slowly varying, which implies that b can be will approximated by a constant in a neighbourhood of each point in the image domain. Energy function has to be minimized within a boundary where the level set evolves. For this a Neumann Boundary condition is defined and is applied to the level set function to get object boundary. Within this specific boundary, the Level Set Evolution process will take place. The level set function is obtained by taking the signed function of randomized image and has values 0, 1, and -1. Local intensity clustering property indicates that the image can be segmented into three regions based on the values of level set function. Standard K-means Criterion is used to classify the local intensity which can be defined as Where K(y-x) is a Gaussian function. During the evolution of level set function ci and the bias field b are updated by minimizing the energy function E(Φ, c, b) whereWhere K(y-x) is a Gaussian function. During the evolution of level set function ci and the bias field b are updated by minimizing the energy function E(Φ, c, b) wherewhere M_i (Φ_x ) is the member ship function which is used as the phase indicator for the regions and H(.) is the heaviside function and represents set of

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