By Tavares J., Jorge R. (eds.)
The current e-book includes prolonged models of papers offered within the overseas convention VIPIMAGE 2007 – ECCOMAS Thematic convention on Computational imaginative and prescient and scientific photo, held in Faculdade de Engenharia da Universidade do Porto, in 17-19 of October 2007. This convention used to be the 1st ECCOMAS thematic convention on computational imaginative and prescient and clinical picture processing. It covers themes comparable with picture processing and research, scientific imaging and computational modeling and simulation, contemplating their multidisciplinary. This publication collects the cutting-edge examine, tools and new rules as regards to computational imaginative and prescient and scientific snapshot processing contributing for the improvement of those parts of data.
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Extra resources for Advances in computational vision and medical image processing
E) Alignment: Alignment of two similar but not identical geometric objects is a difficult problem. There are relatively few papers in the geometric modeling community that address this problem. Recently, an interesting technique was reported by Eckstein et al.  where generalized surface flow was used for non-rigid alignment of a template geometry into the patient data. The authors design an energy function based on pseudo-Hausdorff distance between the two geometries and evolve the template geometry to fit the patient geometry following the gradient of the energy function.
107], and via edge matching technique by Mumford and Shah . 2 Geometry Processing (A) Surface Extraction: Geometry extraction from three dimensional volumetric data is a primary step toward further analysis. There are several approaches for accomplishing this task. 1 Cardiovascular Models 9 Contouring: Isosurfacing is a popular method to extract surface geometry from scalar volume containing intensity values of the scanned anatomy. There are typically two types of contouring method frequently used in the literature – Primal Contouring and Dual Contouring.
Details of this method can be found in . (B) Curation/Filtering: The cardiovascular geometry extracted from imaging data typically has topological anomalies, namely small components, spurious noisy features etc. Therefore a careful investigation and subsequent removal of the spurious features present in the data is essential. Following are different scenarios. Fig. 9 Surface Reconstruction from Point Cloud Data: major components of the human heart are reconstructed using the voxels surrounding the boundaries of the individual regions 1 Cardiovascular Models 11 Regularization: Geometry from volume data is often reconstructed via image segmentation.
Advances in computational vision and medical image processing by Tavares J., Jorge R. (eds.)