Form laporan stok barang.xls8/31/2023 To describe fine detail in the data, we employ local finite element deformations from the model surface. We maintain a relatively simple cross-section function to make this detection straightforward (note that any cross-section function is possible). In addition, the cross-section parameter values of our model may aid in automatically isolating these regions. This information may be used for such tasks as a reformatting of the original image data in order to visually detect stenoses or aneurysms. Given this expressiveness, we are able to provide a second order continuous approximation to the centerline of nearly any tubular object. Unlike all previous formulations, our model is capable of describing a cylinder with an arbitrary spine (a space curve based on cubic B-splines) and arbitrary cross section which is guaranteed to be orthogonal to the spine. We introduce a novel analytic model formulation for recovering cylindrical structures (e.g., blood vessels) from segmented 3-D medical image data.
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