surface_registration

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surface_registration [2022/07/01 01:26] administradorsurface_registration [2022/07/01 01:34] (current) administrador
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 ====== Surface registration ====== ====== Surface registration ======
  
-In image-guided surgery systems, image-to-patient spatial registration is to get the spatial transformation between the image space and the actual operating space. Although the image-to-patient spatial registration methods using paired-point or surface-matching are used in some image-guided neurosurgery systems, the key problem is that the global optimization registration result cannot be achieved. Therefore, this paper proposes a new rotation invariant feature for decoupling rotation and translation space, based on which a global optimization point set registration method is proposed.+In image-guided surgery systems, image-to-patient [[spatial registration]] is to get the spatial transformation between the image space and the actual operating space. Although the image-to-patient spatial registration methods using paired-point or surface-matching are used in some image-guided neurosurgery systems, the key problem is that the global optimization registration result cannot be achieved. Therefore, this paper proposes a new rotation invariant feature for decoupling rotation and translation space, based on which a global optimization point set registration method is proposed.
  
 The new rotation-invariant features, constructed based on the edges and the angles, are the rotation invariant, which has high feature resolution. And some of them are not only the rotation invariant but also the translation invariants. To obtain the global optimal solution, BnB search strategy is used to search the parameter space of the translation and the computational cost is reduced simultaneously. The registration accuracy of the spatial registration method is analyzed by comparing the difference between the estimated transform and the standard transform to calculate the registration error. The new rotation-invariant features, constructed based on the edges and the angles, are the rotation invariant, which has high feature resolution. And some of them are not only the rotation invariant but also the translation invariants. To obtain the global optimal solution, BnB search strategy is used to search the parameter space of the translation and the computational cost is reduced simultaneously. The registration accuracy of the spatial registration method is analyzed by comparing the difference between the estimated transform and the standard transform to calculate the registration error.
  • surface_registration.txt
  • Last modified: 2022/07/01 01:34
  • by administrador