Download PDF by Chandrajit Bajaj, Samrat Goswami (auth.), João Manuel R. S.: Advances in Computational Vision and Medical Image

By Chandrajit Bajaj, Samrat Goswami (auth.), João Manuel R. S. Tavares, R. M. Natal Jorge (eds.)

ISBN-10: 1402090854

ISBN-13: 9781402090851

ISBN-10: 1402090862

ISBN-13: 9781402090868

The current e-book includes prolonged types of papers offered within the foreign convention VIPIMAGE 2007 – ECCOMAS Thematic convention on Computational imaginative and prescient and scientific photograph, held in Faculdade de Engenharia da Universidade do Porto, in 17-19 of October 2007. This convention was once the 1st ECCOMAS thematic convention on computational imaginative and prescient and scientific photograph processing. It covers issues similar with photo processing and research, clinical imaging and computational modeling and simulation, contemplating their multidisciplinary.

This e-book collects the cutting-edge learn, tools and new principles with regards to computational imaginative and prescient and clinical photograph processing contributing for the advance of those parts of knowledge.

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Extra resources for Advances in Computational Vision and Medical Image Processing: Methods and Applications

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IEEE Transactions on Image Processing 8(2) (1998) 220–230 34. : Adaptive contrast enhancement using generalization of histogram equalization. IEEE Transactions on Image Processing 9(5) (2000) 889–906 35. : Properties and performance of a center/surround retinex. IEEE Transactions on Image Processing 6(3) (1997) 451–462 36. : A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Transactions on Image Processing 6(7) (1997) 965–976 37. : Contrast enhancement of medical images using multiscale edge representation.

The value of a good heuristic close to the real distance is revealed by the following theorem. Theorem 5 (Geodesic segment). The function ψ (x) = d(x0 , x) + d(x1 , x) is minimal and constant ψ (x) = d(x0 , x1 ) along the geodesic path joining x0 and x1 . In the setting of graph theory, the Dijkstra algorithm can be replaced by the A∗ (A-star), [19], which uses a heuristic to speed up computations. The following theorem proves the validity of this approach. Theorem 6 (A∗ validity). 1, is a geodesic between x0 and x1 .

In order to describe the algorithm for these two settings (curved triangulated surface embedded in Rk and Riemannian manifold with arbitrary metric H(x) for x ∈ R2 ), we solve the Eikonal equation ||∇xU||H −1 (x) = W (x) locally on the triangle faces f ∈ Fx adjacent to x in order to compute U pdate(x) ≈ U(x). In order to compute the update value at a given vertex x, the algorithm computes an update value U pdate f (x) for each triangle f ∈ Fx in the face 1-ring around x, Fx = { f1 , . . , fk }.

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Advances in Computational Vision and Medical Image Processing: Methods and Applications by Chandrajit Bajaj, Samrat Goswami (auth.), João Manuel R. S. Tavares, R. M. Natal Jorge (eds.)


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