Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_4473_Библиотеки_им_академика_М_И_Перельмана

recursively descending in the neighborhood of them. The identication is based on a lower and an upper threshold depending on the assignment method of the ENT specialist. Based on this seg­mentation, the Marching Cubes algorithm [34] is used to extract the surface of the nasal cavity yielding a three-dimensional triangle representa­tion. This algorithm is based on the intensity detection along voxel edges and denes vertices along these lines by a bilinear interpolation between the intensities at the corners of the vox­els. A set of triangles is dened for such a vertex conguration, which is looked up in a congura­tion table, containing 256 possible combinations. In a post-processing step, the surface is smoothed using a windowed sinc function [35], removing high-frequency noise in Fourier space by apply­ing a transfer function. In a nal step, the surface is split into multiple parts. The nostrils and the throat are separated from the rest of the nasal cav­ity and are smoothed with a Laplace lter until convergence. This lter performs a relaxation of the mesh and iteratively moves all vertices into one plane. This step allows the proper application of the boundary conditions in the ow simula­tion. Based on this model, an automatic Cartesian grid generator creates the computational mesh. A minimal bounding cube is initially placed around the surface. This cube is then continuously split into eight smaller cubes until a user-dened level of renement is reached. During the splitting pro­cess, cells outside the uid domain are removed.