Computational Diffusion MRI, Lauren O`Donnell; Gemma Nedjati-Gilani; Yogesh Rat
Автор: Lauren O`Donnell; Gemma Nedjati-Gilani; Yogesh Rat Название: Computational Diffusion MRI ISBN: 3319363441 ISBN-13(EAN): 9783319363448 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
I. Network Analysis: Vector weights and dual graphs: an emphasis on connections in brain network analysis: Peter Savadjiev, Carl-Fredrik Westin, and Yogesh Rathi.- Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer's disease: Madelaine Daianu, Neda Jahanshad, Julio E. Villalon-Reina, Mario F. Mendez, George Bartzokis, Elvira E. Jimenez, Aditi Joshi, Joseph Barsuglia and Paul M. Thompson.- Parcellation-Independent Multi-Scale Framework for Brain Network Analysis: Markus Schirmer et al.- II. Clinical Applications: Multiple stages classification of Alzheimer's disease based on structural brain networks using Generalized Low Rank Approximations (GLRAM): Zhan L, Nie Z, Ye J, Wang Y, Jin Y, Jahanshad N, Prasad G, de Zubicaray GI, McMahon KL, Martin NG, Wright MJ, Thompson PM.- The added value of diffusion tensor imaging for automated white matter hyperintensity segmentation: Hugo J. Kuijf, Chantal M. W. Tax, L. Karlijn Zaanen, Willem H. Bouvy, Jeroen de Bresser, Alexander Leemans, Max A. Viergever, Geert Jan Biessels, and Koen L. Vincken.- Algebraic connectivity of brain networks shows patterns of segregation leading to reduced network robustness in Alzheimer's disease: Madelaine Daianu, Neda Jahanshad, Talia M. Nir, Cassandra D. Leonardo, Clifford R. Jack, Jr., Michael W. Weiner, Matthew Bernstein and Paul M. Thompson.- Diffusion-Map: A Novel Visualizing Biomarker for Diffusion Tensor Imaging of Human Brain White Matter: Mohammad Hadi Aarabi and Hamidreza Saligheh Rad.- A Multi-Parametric Diffusion Magnetic Resonance Imaging Texture Feature Model for Prostate Cancer Analysis: Farzad Khalvati, Amen Modhafar, Andrew Cameron, Alexander Wong, Masoom A. Haider.- Predicting poststroke depression from brain connectivity: J. Mitra, K-K. Shen, S. Ghose, P. Bourgeat, J. Fripp, O. Salvado, B. Campbell, S. Palmer, L. Carey, S. Rose.- III. Tractography: Fiber Bundle Segmentation Using Spectral Embedding and Supervised Learning: Dorothйe Vercruysse, Daan Christiaens, Frederik Maes, Stefan Sunaert, and Paul Suetens.- Atlas-Guided Global Tractography: Imposing a Prior on the Local Track Orientation: Daan Christiaens, Marco Reisert, Thijs Dhollander, Frederik Maes, Stefan Sunaert, and Paul Suetens.- IV. Q-Space Reconstruction: Magnitude and complex based diffusion signal reconstruction: Marco Pizzolato, Aurobrata Ghosh, Timothй Boutelier, and Rachid Deriche.- Diffusion propagator estimation using Gaussians scattered in q-space: Lipeng Ning, Oleg Michailovich, Carl-Fredrik Westin, Yogesh Rathi.- An Analytical 3D Laplacian Regularized SHORE Basis and its Impact on EAP Reconstruction and Microstructure Recovery: Rutger Fick, Demian Wassermann, Gonzalo Sanguinetti, and Rachid Deriche.- V.Post Processing: Motion is Inevitable: The Impact of Motion Correction Schemes on HARDI Reconstructions: Shireen Elhabian, Yaniv Gur, Clement Vachet, Joseph Piven for IBIS∗, Martin Styner, Ilana Leppert, G. Bruce Pike and Guido Gerig.- Joint Super-Resolution Using Only One Anisotropic Low-Resolution Image per q-Space Coordinate: Vladimir Golkov, Tim Sprenger, Marion I. Menzel, Ek Tsoon Tan, Luca Marinelli, Christopher J. Hardy, Axel Haase, Daniel Cremers, and Jonathan I. Sperl.- Bilateral Filtering of Multiple Fiber Orientations in Diffusion MRI: Ryan P. Cabeen and David H. Laidlaw.- Dictionary Based Super-Resolution for Diffusion MRI: Burak Yoldemir, Mohammad Bajammal, Rafeef Abugharbieh.
Автор: Trappenberg Thomas P. Название: Fundamentals of Computational Neuroscience ISBN: 0199568413 ISBN-13(EAN): 9780199568413 Издательство: Oxford Academ Рейтинг: Цена: 9504.00 р. Наличие на складе: Поставка под заказ.
Описание: The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the first edition. Completely redesigned and revised, it introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain.
Описание: Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system.
Автор: Devadoss Satyan L., O`Rourke Joseph Название: Discrete and Computational Geometry ISBN: 0691145539 ISBN-13(EAN): 9780691145532 Издательство: Wiley Рейтинг: Цена: 11088.00 р. Наличие на складе: Поставка под заказ.
Описание: Offers a comprehensive introduction to discrete geometry. This book covers traditional topics such as convex hulls, triangulations, and Voronoi diagrams, as well as subjects like pseudotriangulations, curve reconstruction, and locked chains. It is suitable for sophomores in mathematics, computer science, engineering, or physics.
Автор: Rylander, Thomas, Ingelstrom, Par, Bondeson, Ander Название: Computational Electromagnetics ISBN: 146145350X ISBN-13(EAN): 9781461453505 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In its expanded second edition, this book describes sources of errors in numerical computations, and provides tools for assessing the accuracy of numerical methods and their solutions. Includes MATLAB programs and detailed description of practical issues.
Автор: Thomas Schultz; Gemma Nedjati-Gilani; Archana Venk Название: Computational Diffusion MRI and Brain Connectivity ISBN: 3319024744 ISBN-13(EAN): 9783319024745 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Part I Acquisition of Diffusion MRI: Comparing Simultaneous Multi-slice Diffusion Acquisitions by Y.Rathi et al.- Effect of Data Acquisition and Analysis Method on Fiber Orientation Estimation in Diffusion MRI by B.Wilkins et al.- Model-based super-resolution of diffusion MRI by A.Tobisch et al.- A quantitative evaluation of errors induced by reduced field-of-view in diffusion tensor imaging by J.Hering et al.- Part II Diffusion MRI Modeling: The Diffusion Dictionary in the Human Brain is Short: Rotation Invariant Learning of Basis Functions by M.Reisert et al.- Diffusion Propagator Estimation Using Radial Basis Functions by Y.Rathi et al.- A Framework for ODF Inference by using Fiber Tract Adaptive MPG Selection by H.Hontani et al.- Non-Negative Spherical Deconvolution (NNSD) for Fiber Orientation Distribution Function Estimation by J.Cheng et al.- Part III Tractography: A Novel Riemannian Metric for Geodesic Tractography in DTI by A.Fuster et al.- Fiberfox: An extensible system for generating realistic white matter software phantoms by P.F.Neher et al.- Choosing a Tractography Algorithm: On the Effects of Measurement Noise by A.Reichenbach et al.- Uncertainty in Tractography via Tract Confidence Regions by C.J.Brown et al.- Estimating Uncertainty in White Matter Tractography Using Wild Non-Local Bootstrap by P.- T. Yap et al.- Part IV Group Studies and Statistical Analysis: Groupwise Deformable Registration of Fiber Track Sets using Track Orientation Distributions by D. Christiaens et al.- Groupwise registration for correcting subject motion and eddy current distortions in diffusion MRI using a PCA based dissimilarity metric by W. Huizinga et al.- Fiber Based Comparison of Whole Brain Tractographies with Application to Amyotrophic Lateral Sclerosis by G. Zimmerman-Moreno et al.- Statistical Analysis of White Matter Integrity for the Clinical Study of Typical Specific Language Impairment in Children by E.Vallйe et al.- Part V Brain Connectivity: Disrupted Brain Connectivity in Alzheimer's Disease: Effects of Network Thresholding: M. Daianu et al.- Rich Club Analysis of Structural Brain Connectivity at 7 Tesla versus 3 Tesla: E. Dennis et al.- Coupled Intrinsic Connectivity: A Principled Method for Exploratory Analysis of Paired Data: D. Scheinost et al.- Power Estimates for Voxel-Based Genetic Association Studies using Diffusion Imaging: N. Jahanshad et al.- Global changes in the connectome in autism spectrum diseases: C. Jonas Goch et al.
Автор: Thomas Schultz; Gemma Nedjati-Gilani; Archana Venk Название: Computational Diffusion MRI and Brain Connectivity ISBN: 3319376845 ISBN-13(EAN): 9783319376844 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Part I Acquisition of Diffusion MRI: Comparing Simultaneous Multi-slice Diffusion Acquisitions by Y.Rathi et al.- Effect of Data Acquisition and Analysis Method on Fiber Orientation Estimation in Diffusion MRI by B.Wilkins et al.- Model-based super-resolution of diffusion MRI by A.Tobisch et al.- A quantitative evaluation of errors induced by reduced field-of-view in diffusion tensor imaging by J.Hering et al.- Part II Diffusion MRI Modeling: The Diffusion Dictionary in the Human Brain is Short: Rotation Invariant Learning of Basis Functions by M.Reisert et al.- Diffusion Propagator Estimation Using Radial Basis Functions by Y.Rathi et al.- A Framework for ODF Inference by using Fiber Tract Adaptive MPG Selection by H.Hontani et al.- Non-Negative Spherical Deconvolution (NNSD) for Fiber Orientation Distribution Function Estimation by J.Cheng et al.- Part III Tractography: A Novel Riemannian Metric for Geodesic Tractography in DTI by A.Fuster et al.- Fiberfox: An extensible system for generating realistic white matter software phantoms by P.F.Neher et al.- Choosing a Tractography Algorithm: On the Effects of Measurement Noise by A.Reichenbach et al.- Uncertainty in Tractography via Tract Confidence Regions by C.J.Brown et al.- Estimating Uncertainty in White Matter Tractography Using Wild Non-Local Bootstrap by P.- T. Yap et al.- Part IV Group Studies and Statistical Analysis: Groupwise Deformable Registration of Fiber Track Sets using Track Orientation Distributions by D. Christiaens et al.- Groupwise registration for correcting subject motion and eddy current distortions in diffusion MRI using a PCA based dissimilarity metric by W. Huizinga et al.- Fiber Based Comparison of Whole Brain Tractographies with Application to Amyotrophic Lateral Sclerosis by G. Zimmerman-Moreno et al.- Statistical Analysis of White Matter Integrity for the Clinical Study of Typical Specific Language Impairment in Children by E.Vallйe et al.- Part V Brain Connectivity: Disrupted Brain Connectivity in Alzheimer's Disease: Effects of Network Thresholding: M. Daianu et al.- Rich Club Analysis of Structural Brain Connectivity at 7 Tesla versus 3 Tesla: E. Dennis et al.- Coupled Intrinsic Connectivity: A Principled Method for Exploratory Analysis of Paired Data: D. Scheinost et al.- Power Estimates for Voxel-Based Genetic Association Studies using Diffusion Imaging: N. Jahanshad et al.- Global changes in the connectome in autism spectrum diseases: C. Jonas Goch et al.
Автор: Andrea Fuster; Aurobrata Ghosh; Enrico Kaden; Yoge Название: Computational Diffusion MRI ISBN: 3319541293 ISBN-13(EAN): 9783319541297 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The MR Physics of Advanced Diffusion Imaging: Matt Hall.- Noise Floor Removal via Phase Correction of Complex Diffusion-Weighted Images: Influence on DTI and q-Space Metrics: M. Pizzolato et al.- Regularized Dictionary Learning with Robust Sparsity Fitting for Compressed Sensing Multishell HARDI: K. Gupta et al.- Denoising Diffusion-Weighted Images Using Grouped Iterative Hard Thresholding of Multi-Channel Framelets: Jian Zhang et al.- Diffusion MRI Signal Augmentation - From Single Shell to Multi Shell with Deep Learning: S. Koppers et al.- Multi-Spherical Diffusion MRI: Exploring Diffusion Time Using Signal Sparsity: R.H.J. Fick et al.- Sensitivity of OGSE ActiveAx to Microstructural Dimensions on a Clinical Scanner: L.S. Kakkar et al.- Groupwise Structural Parcellation of the Cortex: A Sound Approach Based on Logistic Models: G. Gallardo et al.- Robust Construction of Diffusion MRI Atlases with Correction for Inter-Subject Fiber Dispersion: Z. Yang et al.- Parcellation of Human Amygdala Subfields Using Orientation Distribution Function and Spectral K-means Clustering: Q. Wen et al.- Sparse Representation for White Matter Fiber Compression and Calculation of Inter-Fiber Similarity: G. Zimmerman Moreno et al.- An Unsupervised Group Average Cortical Parcellation using Diffusion MRI to Probe Cytoarchitecture: T. Ganepola et al.- Using multiple Diffusion MRI Measures to Predict Alzheimer's Disease with a TV-L1 Prior: J.E. Villalon-Reina et al.- Accurate Diagnosis of SWEDD vs. Parkinson Using Microstructural Changes of Cingulum Bundle: Track-Specific Analysis: F. Rahmani et al.- Colocalization of Functional Activity and Neurite Density within Cortical Areas: A. Teillac et al.- Comparison of Biomarkers in Transgenic Alzheimer Rats Using Multi-shell Diffusion MRI: R.H.J. Fick.- Working Memory Function in Recent-onset Schizophrenia Patients Associated with White Matter Microstructure: Connectometry Approach: M. Dolatshahi et al.
Описание: The Finite Volume Method in Computational Fluid Dynamics
Автор: Haber Название: Computational Methods in Geophysical Electromagnetics ISBN: 1611973791 ISBN-13(EAN): 9781611973792 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 10395.00 р. Наличие на складе: Нет в наличии.
Описание: Bridging the gap between theory and applications, this monograph provides a framework for the solution of electromagnetic imaging problems in geophysics. It provides a simple explanation of finite volume discretization; a full description of the basic concepts for solving inverse problems through optimization; a summary of applied electromagnetics methods; and MATLAB® code for efficient computation. The book will appeal to students and practitioners interested in computational science, data fitting, and applications to electromagnetics.
Автор: Strang Название: Computational Science and Engineering ISBN: 0961408812 ISBN-13(EAN): 9780961408817 Издательство: Cambridge Academ Рейтинг: Цена: 16471.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Encompasses the full range of computational science and engineering from modelling to solution, both analytical and numerical. It develops a framework for the equations and numerical methods of applied mathematics. Gilbert Strang has taught this material to thousands of engineers and scientists (and many more on MIT's OpenCourseWare 18.085-6). His experience is seen in his clear explanations, wide range of examples, and teaching method. The book is solution-based and not formula-based: it integrates analysis and algorithms and MATLAB codes to explain each topic as effectively as possible. The topics include applied linear algebra and fast solvers, differential equations with finite differences and finite elements, Fourier analysis and optimization. This book also serves as a reference for the whole community of computational scientists and engineers. Supporting resources, including MATLAB codes, problem solutions and video lectures from Gilbert Strang's 18.085 courses at MIT, are provided at math.mit.edu/cse.
Автор: Tomasz Kaczynski, Konstantin Mischaikow, Marian Mr Название: Computational Homology ISBN: 1441923543 ISBN-13(EAN): 9781441923547 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Homology is a powerful tool used by mathematicians to study the properties of spaces and maps that are insensitive to small perturbations. Following this is a section containing extensions to further developments in algebraic topology, applications to computational dynamics, and applications to image processing.
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