J Med Syst - A new method for 3D thinning of hybrid shaped porous media using artificial intelligence. Application to trabecular bone.

Tópicos

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Resumo

Curve and surface thinning are widely-used skeletonization techniques for modeling objects in three dimensions. In the case of disordered porous media analysis, however, neither is really efficient since the internal geometry of the object is usually composed of both rod and plate shapes. This paper presents an alternative to compute a hybrid shape-dependent skeleton and its application to porous media. The resulting skeleton combines 2D surfaces and 1D curves to represent respectively the plate-shaped and rod-shaped parts of the object. For this purpose, a new technique based on neural networks is proposed: cascade combinations of complex wavelet transform (CWT) and complex-valued artificial neural network (CVANN). The ability of the skeleton to characterize hybrid shaped porous media is demonstrated on a trabecular bone sample. Results show that the proposed method achieves high accuracy rates about 99.78%-99.97%. Especially, CWT (2nd level)-CVANN structure converges to optimum results as high accuracy rate-minimum time consumption.

Resumo Limpo

curv surfac thin widelyus skeleton techniqu model object three dimens case disord porous media analysi howev neither realli effici sinc intern geometri object usual compos rod plate shape paper present altern comput hybrid shapedepend skeleton applic porous media result skeleton combin d surfac d curv repres respect plateshap rodshap part object purpos new techniqu base neural network propos cascad combin complex wavelet transform cwt complexvalu artifici neural network cvann abil skeleton character hybrid shape porous media demonstr trabecular bone sampl result show propos method achiev high accuraci rate especi cwt nd levelcvann structur converg optimum result high accuraci rateminimum time consumpt

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