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101 MRI brain solutions / / editors, Hariqbal Singh, Rangankar Varsha, Santosh Konde
| 101 MRI brain solutions / / editors, Hariqbal Singh, Rangankar Varsha, Santosh Konde |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | New Delhi, India : , : Jaypee, , 2015 |
| Descrizione fisica | 1 online resource (285 p.) |
| Disciplina | 616.8047548 |
| Soggetto topico | Brain - Magnetic resonance imaging |
| Soggetto genere / forma | Electronic books. |
| ISBN | 93-85999-40-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Intro; Prelims; Chapter-01_Physical Principle of Magnetic Resonance Imaging; Chapter-02_Anatomy of Brain; Chapter-03_Congenital; Chapter-04_Infections; Chapter-05_Vascular in Origin; Chapter-06_White Matter Disease; Chapter-07_Neurocutaneous Syndrome; Chapter-08_Tumor and Tumor Like Lesions; Chapter-09_Metabolic Lesions; Chapter-10_Artifacts; Chapter-11_Miscellaneous; Chapter-12_Glossary of MRI Terms; Chapter-13_MRI Acronyms; Index |
| Record Nr. | UNINA-9910465861903321 |
| New Delhi, India : , : Jaypee, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
101 MRI brain solutions / / editors, Hariqbal Singh, Rangankar Varsha, Santosh Konde
| 101 MRI brain solutions / / editors, Hariqbal Singh, Rangankar Varsha, Santosh Konde |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | New Delhi, India : , : Jaypee, , 2015 |
| Descrizione fisica | 1 online resource (285 p.) |
| Disciplina | 616.8047548 |
| Soggetto topico | Brain - Magnetic resonance imaging |
| ISBN | 93-85999-40-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Intro; Prelims; Chapter-01_Physical Principle of Magnetic Resonance Imaging; Chapter-02_Anatomy of Brain; Chapter-03_Congenital; Chapter-04_Infections; Chapter-05_Vascular in Origin; Chapter-06_White Matter Disease; Chapter-07_Neurocutaneous Syndrome; Chapter-08_Tumor and Tumor Like Lesions; Chapter-09_Metabolic Lesions; Chapter-10_Artifacts; Chapter-11_Miscellaneous; Chapter-12_Glossary of MRI Terms; Chapter-13_MRI Acronyms; Index |
| Record Nr. | UNINA-9910798005703321 |
| New Delhi, India : , : Jaypee, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
101 MRI brain solutions / / editors, Hariqbal Singh, Rangankar Varsha, Santosh Konde
| 101 MRI brain solutions / / editors, Hariqbal Singh, Rangankar Varsha, Santosh Konde |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | New Delhi, India : , : Jaypee, , 2015 |
| Descrizione fisica | 1 online resource (285 p.) |
| Disciplina | 616.8047548 |
| Soggetto topico | Brain - Magnetic resonance imaging |
| ISBN | 93-85999-40-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Intro; Prelims; Chapter-01_Physical Principle of Magnetic Resonance Imaging; Chapter-02_Anatomy of Brain; Chapter-03_Congenital; Chapter-04_Infections; Chapter-05_Vascular in Origin; Chapter-06_White Matter Disease; Chapter-07_Neurocutaneous Syndrome; Chapter-08_Tumor and Tumor Like Lesions; Chapter-09_Metabolic Lesions; Chapter-10_Artifacts; Chapter-11_Miscellaneous; Chapter-12_Glossary of MRI Terms; Chapter-13_MRI Acronyms; Index |
| Record Nr. | UNINA-9910809983203321 |
| New Delhi, India : , : Jaypee, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The 3D Stereotaxic Brain Atlas of the Degu [[electronic resource] ] : With MRI and Histology Digital Model with a Freely Rotatable Viewer / / by Noriko Kumazawa-Manita, Tsutomu Hashikawa, Atsushi Iriki
| The 3D Stereotaxic Brain Atlas of the Degu [[electronic resource] ] : With MRI and Histology Digital Model with a Freely Rotatable Viewer / / by Noriko Kumazawa-Manita, Tsutomu Hashikawa, Atsushi Iriki |
| Autore | Kumazawa-Manita Noriko |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Tokyo : , : Springer Japan : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (149 pages) |
| Disciplina | 616.8047548 |
| Collana | Brain Science |
| Soggetto topico |
Neurosciences
Behavioral sciences Animal anatomy Human physiology Behavioral Sciences Animal Anatomy / Morphology / Histology Human Physiology |
| ISBN | 4-431-56615-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: Introduction, Materials and Methods, and References -- Chapter 2: List of Structures -- Chapter 3: The Degu Brain Atlas -- Chapter 4: SG-eye Operation Manual -- Index of Structures and Abbreviations. |
| Record Nr. | UNINA-9910298409803321 |
Kumazawa-Manita Noriko
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| Tokyo : , : Springer Japan : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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7.0 Tesla MRI Brain Atlas [[electronic resource] ] : In-vivo Atlas with Cryomacrotome Correlation / / edited by Zang-Hee Cho
| 7.0 Tesla MRI Brain Atlas [[electronic resource] ] : In-vivo Atlas with Cryomacrotome Correlation / / edited by Zang-Hee Cho |
| Edizione | [2nd ed. 2015.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (569 p.) |
| Disciplina | 616.8047548 |
| Soggetto topico |
Neuroradiology
Neurosciences Radiology Neurosurgery Imaging / Radiology |
| ISBN | 3-642-54398-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Foreword -- Preface -- Preface of the 2nd Edition -- Introduction -- 1. Reference of Brain Image Setting -- 2. Orientation of Brain Images -- I. Orientation of the image sections and planes -- II. Standard of the sectional brain image planes and sizes -- III. Adjustment of MRI brain to the reference brain -- IV. Terminology & Labeling -- V. Data collection system for clinicopathologic brain mapping -- VI. Figures (Figs. 1, 2, 3) -- 3. Sources of Brain Images -- I. In vivo Images using 7.0T MRI -- II. Cadaver Images by Cryomacrotome -- III. Image reconstruction and volume rendering -- 4. 3D Images by Volume Rendering -- I. Coronal, Sagittal and Axial Cuts- Cadaver (Fig. 4) -- II. Coronal, Sagittal and Axial Cuts- MRI (Fig. 5) -- III. Sulcus and Gyrus- MRI (Fig. 6) -- IV.Brodmann areas-MRI (Fig. 7) -- Acknowledgements -- Chapter I. Coronal Images of Cadaver & Human Brain of 7.0T MRI In Vivo -- Chapter II. Sagittal Images of Cadaver & Human Brain of 7.0T MRI In Vivo -- Chapter III. Axial Images of Cadaver & Human Brain of 7.0T MRI In Vivo -- References -- Abbreviations -- Index. |
| Record Nr. | UNINA-9910300208403321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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7.0 Tesla MRI Brain White Matter Atlas [[electronic resource] /] / edited by Zang-Hee Cho
| 7.0 Tesla MRI Brain White Matter Atlas [[electronic resource] /] / edited by Zang-Hee Cho |
| Edizione | [2nd ed. 2015.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (478 p.) |
| Disciplina | 616.8047548 |
| Soggetto topico |
Radiology
Neuroradiology Neurosciences Neurosurgery Imaging / Radiology |
| ISBN | 3-642-54392-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- 1. MR Diffusion Tensor Imaging (DTI) and Track-Density Imaging (TDI) -- a. MR Diffusion Tensor Imaging (DTI) and Super-Resolution Track-Density Imaging (TDI) -- b. Track-Density Imaging (TDI) – Examples of DTI and TDI-1 -- 2. Views, Directions, and Orientations of Brain Images -- a. Views and Directions of the Brain Image -- b. Definition of the Central Intercommissural Line -- c. Volume Rendered 3D Images -- Acknowledgments -- PART 1. Coronal Images of Tractography and Corresponding In-Vivo 7.0-T MRI Anatomy -- PART 2. Sagittal Images of Tractography and Corresponding In-Vivo 7.0-T MRI Anatomy -- PART 3. Axial Images of Tractography and Corresponding In-Vivo 7.0-T MRI Anatomy. |
| Record Nr. | UNINA-9910300209703321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Adolescent Brain Cognitive Development Neurocognitive Prediction [[electronic resource] ] : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru
| Adolescent Brain Cognitive Development Neurocognitive Prediction [[electronic resource] ] : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 188 p. 57 illus., 49 illus. in color.) |
| Disciplina | 616.8047548 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Machine learning Mathematical statistics Data mining Image Processing and Computer Vision Machine Learning Probability and Statistics in Computer Science Data Mining and Knowledge Discovery |
| ISBN | 3-030-31901-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Combined Deep Learning-Gradient Boosting Machine Framework for Fluid Intelligence Prediction -- Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet -- Deep Learning vs. Classical Machine Learning: A Comparison of Methods for Fluid Intelligence Prediction -- Surface-based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019 -- Prediction of Fluid Intelligence From T1-Weighted Magnetic Resonance Images -- Ensemble of SVM, Random-Forest and the BSWiMS Method to Predict and Describe Structural Associations with Fluid Intelligence Scores from T1-Weighed MRI -- Predicting intelligence based on cortical WM/GM contrast, cortical thickness and volumetry -- Predict Fluid Intelligence of Adolescent Using Ensemble Learning -- Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach -- Predicting Fluid intelligence from structural MRI using Random Forest regression -- Nu Support Vector Machine in Prediction of Fluid Intelligence Using MRI Data -- An AutoML Approach for the Prediction of Fluid Intelligence From MRI-Derived Features -- Predicting Fluid Intelligence from MRI images with Encoder-decoder Regularization -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology -- Ensemble Modeling of Neurocognitive Performance Using MRI-derived Brain Structure Volumes -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression -- Predicting fluid intelligence using anatomical measures within functionally defined brain networks -- Sex differences in predicting fluid intelligence of adolescent brain from T1-weighted MRIs -- Ensemble of 3D CNN regressors with data fusion for fluid intelligence prediction -- Adolescent fluid intelligence prediction from regional brain volumes and cortical curvatures using BlockPC-XGBoost -- Cortical and Subcortical Contributions to Predicting Intelligence using 3D ConvNets. |
| Record Nr. | UNISA-996466429903316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Adolescent Brain Cognitive Development Neurocognitive Prediction : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru
| Adolescent Brain Cognitive Development Neurocognitive Prediction : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 188 p. 57 illus., 49 illus. in color.) |
| Disciplina | 616.8047548 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Machine learning Computer science - Mathematics Mathematical statistics Data mining Computer Vision Machine Learning Probability and Statistics in Computer Science Data Mining and Knowledge Discovery |
| ISBN | 3-030-31901-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Combined Deep Learning-Gradient Boosting Machine Framework for Fluid Intelligence Prediction -- Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet -- Deep Learning vs. Classical Machine Learning: A Comparison of Methods for Fluid Intelligence Prediction -- Surface-based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019 -- Prediction of Fluid Intelligence From T1-Weighted Magnetic Resonance Images -- Ensemble of SVM, Random-Forest and the BSWiMS Method to Predict and Describe Structural Associations with Fluid Intelligence Scores from T1-Weighed MRI -- Predicting intelligence based on cortical WM/GM contrast, cortical thickness and volumetry -- Predict Fluid Intelligence of Adolescent Using Ensemble Learning -- Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach -- Predicting Fluid intelligence from structural MRI using Random Forest regression -- Nu Support Vector Machine in Prediction of Fluid Intelligence Using MRI Data -- An AutoML Approach for the Prediction of Fluid Intelligence From MRI-Derived Features -- Predicting Fluid Intelligence from MRI images with Encoder-decoder Regularization -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology -- Ensemble Modeling of Neurocognitive Performance Using MRI-derived Brain Structure Volumes -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression -- Predicting fluid intelligence using anatomical measures within functionally defined brain networks -- Sex differences in predicting fluid intelligence of adolescent brain from T1-weighted MRIs -- Ensemble of 3D CNN regressors with data fusion for fluid intelligence prediction -- Adolescent fluid intelligence prediction from regional brain volumes and cortical curvatures using BlockPC-XGBoost -- Cortical and Subcortical Contributions to Predicting Intelligence using 3D ConvNets. |
| Record Nr. | UNINA-9910349275503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Cyto- and Myeloarchitectural Brain Atlas of the Ferret (Mustela putorius) in MRI Aided Stereotaxic Coordinates / / by Susanne Radtke-Schuller
| Cyto- and Myeloarchitectural Brain Atlas of the Ferret (Mustela putorius) in MRI Aided Stereotaxic Coordinates / / by Susanne Radtke-Schuller |
| Autore | Radtke-Schuller Susanne |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (380 pages) |
| Disciplina | 616.8047548 |
| Soggetto topico |
Neurosciences
Animal anatomy Animal Anatomy / Morphology / Histology |
| ISBN | 3-319-76626-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Methods -- Index of Brain Structures -- Surface Views of the Ferret Brain -- Atlas Plates with Sub-Panels. . |
| Record Nr. | UNINA-9910298407003321 |
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Radtke-Schuller Susanne
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Diffusion-Weighted MR Imaging of the Brain, Head and Neck, and Spine / / edited by Toshio Moritani, Aristides A. Capizzano
| Diffusion-Weighted MR Imaging of the Brain, Head and Neck, and Spine / / edited by Toshio Moritani, Aristides A. Capizzano |
| Edizione | [3rd ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (931 pages) |
| Disciplina | 616.8047548 |
| Soggetto topico |
Nervous system - Radiography
Neurology Nervous system - Surgery Neuroradiology Neurosurgery Ressonància magnètica Malalties cerebrals Malalties del sistema nerviós central Coll Cap Cervell Columna vertebral |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-62120-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Basics of Diffusion Measurements by MRI -- Diffusion-Weighted and Tensor Imaging of the Normal Brain -- Pitfalls and Artifacts of DW Imaging -- Brain Edema -- Infarction -- Intracranial Hemorrhage -- Vasculopathy and Vasculitis -- Epilepsy -- Demyelinating and Degenerative Diseases -- Toxic and Metabolic Diseases -- Infectious Diseases -- Trauma -- Brain Neoplasms -- Pediatrics -- Head and Neck -- Spine and spinal cord -- How to Use This Book. |
| Record Nr. | UNINA-9910484583403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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