Deformable Models [electronic resource] : Theory and Biomaterial Applications / by Jasjit S. Suri, Aly A. Farag.

By: Suri, Jasjit S [author.]Contributor(s): Farag, Aly A [author.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Topics in Biomedical Engineering. International Book Series: Publisher: New York, NY : Springer New York, 2007Description: XVI, 584p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9780387683430Subject(s): Engineering | Radiology, Medical | Information theory | Biomedical engineering | Engineering | Biomedical Engineering | Imaging / Radiology | Theory of ComputationAdditional physical formats: Printed edition:: No titleDDC classification: 610.28 LOC classification: R856-857Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: Deformable Models: Theory and Biomaterial Applications is the second installation in the two-volume set Deformable Models which provides a wide cross-section of the methods and algorithms of variational and PDE methods in biomedical image analysis. The chapters are written by well-known researchers in this field, and the presentation style goes beyond an intricate abstraction of the theory into real application of the methods and description of the algorithms that were implemented. As such these chapters will serve the main goal of the editors of the volumes in bringing down to earth the latest in variational and PDE methods in modeling of soft tissues, covering the theory, algorithms, and applications of level sets and deformable models in medical image analysis. Overall, the chapters of this volume provide an elegant cross-section of the theory and application of variational and PDE approaches in medical image analysis. Graduate students and researchers at various levels of familiarity with these techniques will find the volume very useful for understanding the theory and algorithmic implementations. In addition, the various case studies provided demonstrate the power of these techniques in clinical applications. Researchers at various levels will find these chapters useful to understand the theory, algorithms, and implementation of many of these approaches.
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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.

Deformable Models: Theory and Biomaterial Applications is the second installation in the two-volume set Deformable Models which provides a wide cross-section of the methods and algorithms of variational and PDE methods in biomedical image analysis. The chapters are written by well-known researchers in this field, and the presentation style goes beyond an intricate abstraction of the theory into real application of the methods and description of the algorithms that were implemented. As such these chapters will serve the main goal of the editors of the volumes in bringing down to earth the latest in variational and PDE methods in modeling of soft tissues, covering the theory, algorithms, and applications of level sets and deformable models in medical image analysis. Overall, the chapters of this volume provide an elegant cross-section of the theory and application of variational and PDE approaches in medical image analysis. Graduate students and researchers at various levels of familiarity with these techniques will find the volume very useful for understanding the theory and algorithmic implementations. In addition, the various case studies provided demonstrate the power of these techniques in clinical applications. Researchers at various levels will find these chapters useful to understand the theory, algorithms, and implementation of many of these approaches.

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