Statistical and computational methods in brain image analysis:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton
CRC Press, Taylor & Francis Group
[2014]
|
| Schriftenreihe: | Chapman & Hall/CRC mathematical and computational imaging sciences
|
| Schlagworte: | |
| Online-Zugang: | TUM01 |
| Beschreibung: | 1 Online-Ressource (xvi, 396 Seiten, 15 ungezählte Seiten) Illustrationen, Diagramme |
| ISBN: | 1299710573 9781299710573 9781439836361 1439836361 |
Internformat
MARC
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| 100 | 1 | |a Chung, Moo K. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Statistical and computational methods in brain image analysis |c Moo K. Chung |
| 264 | 1 | |a Boca Raton |b CRC Press, Taylor & Francis Group |c [2014] | |
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| 505 | 8 | |a "The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLABʼ and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author's website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics."-- | |
| 505 | 8 | |a Includes bibliographical references | |
| 505 | 8 | |a Introduction to brain and medical images -- Bernoulli models for binary images -- General linear models -- Gaussian kernel smoothing -- Random fields theory -- Anisotropic kernel smoothing -- Multivariate general linear models -- Cortical surface analysis -- Heat kernel smoothing on surfaces -- 1Cosine series representation of 3D curves -- Weighted spherical harmonic representation -- Multivariate surface shape analysis -- Laplace-Beltrami Eigenfunctions for surface data -- Persistent homology -- Sparse networks -- Sparse shape models -- Modeling structural brain networks -- Mixed effects models | |
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| 650 | 4 | |a Data Interpretation, Statistical | |
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| 650 | 7 | |a SCIENCE / Life Sciences / Neuroscience |2 bisacsh | |
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| 650 | 4 | |a Innere Medizin | |
| 650 | 4 | |a Medizin | |
| 650 | 4 | |a Brain |x Imaging | |
| 650 | 4 | |a Brain |x Imaging |x Statistical methods | |
| 650 | 4 | |a Brain mapping |x Statistical methods | |
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Datensatz im Suchindex
| _version_ | 1804175029204680704 |
|---|---|
| any_adam_object | |
| author | Chung, Moo K. |
| author_facet | Chung, Moo K. |
| author_role | aut |
| author_sort | Chung, Moo K. |
| author_variant | m k c mk mkc |
| building | Verbundindex |
| bvnumber | BV042796306 |
| collection | ZDB-4-NLEBK |
| contents | "The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLABʼ and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author's website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics."-- Includes bibliographical references Introduction to brain and medical images -- Bernoulli models for binary images -- General linear models -- Gaussian kernel smoothing -- Random fields theory -- Anisotropic kernel smoothing -- Multivariate general linear models -- Cortical surface analysis -- Heat kernel smoothing on surfaces -- 1Cosine series representation of 3D curves -- Weighted spherical harmonic representation -- Multivariate surface shape analysis -- Laplace-Beltrami Eigenfunctions for surface data -- Persistent homology -- Sparse networks -- Sparse shape models -- Modeling structural brain networks -- Mixed effects models |
| ctrlnum | (ZDB-4-NLEBK)935000 (OCoLC)851696122 (DE-599)BVBBV042796306 |
| dewey-full | 616.8/04754 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 616 - Diseases |
| dewey-raw | 616.8/04754 |
| dewey-search | 616.8/04754 |
| dewey-sort | 3616.8 44754 |
| dewey-tens | 610 - Medicine and health |
| discipline | Medizin |
| format | Electronic eBook |
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| id | DE-604.BV042796306 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:09:47Z |
| institution | BVB |
| isbn | 1299710573 9781299710573 9781439836361 1439836361 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028226077 |
| oclc_num | 851696122 |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource (xvi, 396 Seiten, 15 ungezählte Seiten) Illustrationen, Diagramme |
| psigel | ZDB-4-NLEBK ZDB-4-NLEBK TUM_PDA_EBSCOMED_Kauf |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | CRC Press, Taylor & Francis Group |
| record_format | marc |
| series2 | Chapman & Hall/CRC mathematical and computational imaging sciences |
| spelling | Chung, Moo K. Verfasser aut Statistical and computational methods in brain image analysis Moo K. Chung Boca Raton CRC Press, Taylor & Francis Group [2014] 1 Online-Ressource (xvi, 396 Seiten, 15 ungezählte Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Chapman & Hall/CRC mathematical and computational imaging sciences "The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLABʼ and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author's website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics."-- Includes bibliographical references Introduction to brain and medical images -- Bernoulli models for binary images -- General linear models -- Gaussian kernel smoothing -- Random fields theory -- Anisotropic kernel smoothing -- Multivariate general linear models -- Cortical surface analysis -- Heat kernel smoothing on surfaces -- 1Cosine series representation of 3D curves -- Weighted spherical harmonic representation -- Multivariate surface shape analysis -- Laplace-Beltrami Eigenfunctions for surface data -- Persistent homology -- Sparse networks -- Sparse shape models -- Modeling structural brain networks -- Mixed effects models Brain / anatomy & histology Data Interpretation, Statistical Neuroimaging MATHEMATICS / Probability & Statistics / General bisacsh SCIENCE / Life Sciences / Neuroscience bisacsh TECHNOLOGY & ENGINEERING / Biomedical bisacsh HEALTH & FITNESS / Diseases / General bisacsh MEDICAL / Clinical Medicine bisacsh MEDICAL / Diseases bisacsh MEDICAL / Evidence-Based Medicine bisacsh MEDICAL / Internal Medicine bisacsh Evidenz-basierte Medizin Innere Medizin Medizin Brain Imaging Brain Imaging Statistical methods Brain mapping Statistical methods Erscheint auch als Druck-Ausgabe, Hardcover 978-1-4398-3635-4 Erscheint auch als Druck-Ausgabe, Hardcover 1-4398-3635-3 |
| spellingShingle | Chung, Moo K. Statistical and computational methods in brain image analysis "The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLABʼ and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author's website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics."-- Includes bibliographical references Introduction to brain and medical images -- Bernoulli models for binary images -- General linear models -- Gaussian kernel smoothing -- Random fields theory -- Anisotropic kernel smoothing -- Multivariate general linear models -- Cortical surface analysis -- Heat kernel smoothing on surfaces -- 1Cosine series representation of 3D curves -- Weighted spherical harmonic representation -- Multivariate surface shape analysis -- Laplace-Beltrami Eigenfunctions for surface data -- Persistent homology -- Sparse networks -- Sparse shape models -- Modeling structural brain networks -- Mixed effects models Brain / anatomy & histology Data Interpretation, Statistical Neuroimaging MATHEMATICS / Probability & Statistics / General bisacsh SCIENCE / Life Sciences / Neuroscience bisacsh TECHNOLOGY & ENGINEERING / Biomedical bisacsh HEALTH & FITNESS / Diseases / General bisacsh MEDICAL / Clinical Medicine bisacsh MEDICAL / Diseases bisacsh MEDICAL / Evidence-Based Medicine bisacsh MEDICAL / Internal Medicine bisacsh Evidenz-basierte Medizin Innere Medizin Medizin Brain Imaging Brain Imaging Statistical methods Brain mapping Statistical methods |
| title | Statistical and computational methods in brain image analysis |
| title_auth | Statistical and computational methods in brain image analysis |
| title_exact_search | Statistical and computational methods in brain image analysis |
| title_full | Statistical and computational methods in brain image analysis Moo K. Chung |
| title_fullStr | Statistical and computational methods in brain image analysis Moo K. Chung |
| title_full_unstemmed | Statistical and computational methods in brain image analysis Moo K. Chung |
| title_short | Statistical and computational methods in brain image analysis |
| title_sort | statistical and computational methods in brain image analysis |
| topic | Brain / anatomy & histology Data Interpretation, Statistical Neuroimaging MATHEMATICS / Probability & Statistics / General bisacsh SCIENCE / Life Sciences / Neuroscience bisacsh TECHNOLOGY & ENGINEERING / Biomedical bisacsh HEALTH & FITNESS / Diseases / General bisacsh MEDICAL / Clinical Medicine bisacsh MEDICAL / Diseases bisacsh MEDICAL / Evidence-Based Medicine bisacsh MEDICAL / Internal Medicine bisacsh Evidenz-basierte Medizin Innere Medizin Medizin Brain Imaging Brain Imaging Statistical methods Brain mapping Statistical methods |
| topic_facet | Brain / anatomy & histology Data Interpretation, Statistical Neuroimaging MATHEMATICS / Probability & Statistics / General SCIENCE / Life Sciences / Neuroscience TECHNOLOGY & ENGINEERING / Biomedical HEALTH & FITNESS / Diseases / General MEDICAL / Clinical Medicine MEDICAL / Diseases MEDICAL / Evidence-Based Medicine MEDICAL / Internal Medicine Evidenz-basierte Medizin Innere Medizin Medizin Brain Imaging Brain Imaging Statistical methods Brain mapping Statistical methods |
| work_keys_str_mv | AT chungmook statisticalandcomputationalmethodsinbrainimageanalysis |