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: Some probability problems are so difficult that they stump the smartest mathematicians. But even the hardest of these problems can often be solved with a computer and a Monte Carlo simulation, in which a random-number generator simulates a physical process, such as a million rolls of a pair of dice. This is what Digital Dice is all about: how to ge
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.
Описание: Presents the basics of functional analysis, as well as elements of variational equations (on the basis of bi-linear forms), including the Vishik-Lax-Milgram theorem and of generalized solutions of eliptic problems. Sobolev spaces and embedding theorems are introduced.
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.
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: Lauren O`Donnell; Gemma Nedjati-Gilani; Yogesh Rat Название: Computational Diffusion MRI ISBN: 3319111817 ISBN-13(EAN): 9783319111810 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: 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: 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: 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: Wanpracha Chaovalitwongse; Panos Pardalos; Petros Название: Computational Neuroscience ISBN: 1461425999 ISBN-13(EAN): 9781461425991 Издательство: Springer Рейтинг: Цена: 27951.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume includes contributions from numerous disciplines, bridging a vital gap between the mathematical sciences and neuroscience research. This book demonstrates how methods from data mining, signal processing, optimization and cutting-edge medical techniques can be used to tackle the most challenging modern neuroscience problems.
Автор: Martinez Wendy L. Название: Computational Statistics Handbook with MATLAB ISBN: 1466592737 ISBN-13(EAN): 9781466592735 Издательство: Taylor&Francis Рейтинг: Цена: 16078.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
A Strong Practical Focus on Applications and Algorithms Computational Statistics Handbook with MATLAB(R), Third Edition covers today's most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. The text keeps theoretical concepts to a minimum, emphasizing the implementation of the methods.
New to the Third Edition This third edition is updated with the latest version of MATLAB and the corresponding version of the Statistics and Machine Learning Toolbox. It also incorporates new sections on the nearest neighbor classifier, support vector machines, model checking and regularization, partial least squares regression, and multivariate adaptive regression splines.
Web Resource The authors include algorithmic descriptions of the procedures as well as examples that illustrate the use of algorithms in data analysis. The MATLAB code, examples, and data sets are available online.
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