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Deformable Models Theory And Biomaterial Applications at Meripustak

Deformable Models Theory And Biomaterial Applications by Aly Farag , Springer

Books from same Author: Aly Farag

Books from same Publisher: Springer

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  • General Information  
    Author(s)Aly Farag
    PublisherSpringer
    ISBN9780387312040
    Pages581
    BindingMixed media product
    LanguageEnglish
    Publish YearAugust 2007

    Description

    Springer Deformable Models Theory And Biomaterial Applications by Aly Farag

    This book covers the complete spectrum of deformable models, its evolution as an imagery field and its use in many biomedical engineering and clinical application disciplines. The book focuses on the core image processing techniques, theory and biomaterials useful to research and industry. Contributors are all pioneers in the field._x000D_ _x000D_ T-Surfaces Framework For Offset Generation And Semiautomatic 3d Segmentation.- Parametric Contour Model In Medical Image Segmentation.- Deformable Models And Their Application In Segmentation Of Imaged Pathology Specimens.- Image Segmentation Using The Level Set Method.- Parallel Co-Volume Subjective Surface Method For 3d Medical Image Segmentation.- Volumetric Segmentation Using Shape Models In The Level Set Framework.- Medical Image Segmentation Based On Deformable Models And Its Applications.- Breast Strain Imaging: A Cad Framework.- Alternate Spaces For Model Deformation: Application Of Stop And Go Active Models To Medical Images.- Deformable Model-Based Segmentation Of The Prostate From Ultrasound Images.- Segmentation Of Brain Mr Images Using J-Divergence Based Active Contour Models.- Morphometric Analysis Of Normal And Pathologic Brain Structure Via High-Dimensional Shape Transformations.- Efficient Kernel Density Estimation Of Shape And Intensity Priors For Level Set Segmentation.- Volumetric Mri Analysis Of Dyslexic Subjects Using A Level Set Framework.- Analysis Of 4-D Cardiac Mr Data With Nurbs Deformable Models: Temporal Fitting Strategy And Nonrigid Registration.- Robust Neuroimaging-Based Classification Techniques Of Autistic Vs. Typically Developing Brain._x000D_



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