Pathological Brain Detection (eBook)
XXVI, 214 Seiten
Springer Singapore (Verlag)
978-981-10-4026-9 (ISBN)
This book provides detailed practical guidelines on how to develop an efficient pathological brain detection system, reflecting the latest advances in the computer-aided diagnosis of structural magnetic resonance brain images. Matlab codes are provided for most of the functions described. In addition, the book equips readers to easily develop the pathological brain detection system further on their own and apply the technologies to other research fields, such as Alzheimer's detection, multiple sclerosis detection, etc.
Dr. Shui-Hua Wang received her B.S. degree from Southeast University in 2008 and an M.S. from the City University of New York in 2012. She received her Ph.D. from Nanjing University in 2016. She is currently an assistant professor at Nanjing Normal University, and a visiting researcher in University of Leicester, UK. She serves as the editor of Journal of Alzheimer's disease. In the past, she served as the guest lead editor of International Journal of Biomedical Imaging and Multimedia Tools and Application.
Prof. Dr. Yu-Dong Zhang received his B.S. and M.S. degrees from Nanjing University of Aeronautics and Astronautics in 2004 and 2007. He received his Ph.D. degree in Signal and Information Processing from Southeast University in 2010. From 2010 to 2012, he worked at Columbia University as a postdoc. From 2012 to 2013, he worked as a research scientist at Columbia University and New York State Psychiatric Institute. From 2013 to 2017, he worked as a full professor and doctoral advisor at School of computer science and technology at Nanjing Normal University. From 2018, he is a full Professor in Department of Informatics, University of Leicester, UK. His research interests include biomedical image processing, pattern recognition, and artificial intelligence.
Prof. Dr. Zhengchao Dong is a former Associate Professor of Translational Imaging at Columbia University, USA. Having also served at New York State Psychiatry Institute, USA, he has published over 20 papers on JAMA Psychiatry, Progress in Nuclear Magnetic Resonance Spectroscopy, Neuropsychopharmacology, Neuroimages, Human Brain Mapping, etc.
Preetha Phillips is currently pursuing her Doctor of Osteopathic Medicine degree at West Virginia School of Osteopathic Medicine. She received her B.S. degree from Shepherd University in May 2016. She has conducted research on using magnetic resonance spectroscopy (MRS) to diagnose panic disorder, and on the analysis of pain mechanisms in rats.
This book provides detailed practical guidelines on how to develop an efficient pathological brain detection system, reflecting the latest advances in the computer-aided diagnosis of structural magnetic resonance brain images. Matlab codes are provided for most of the functions described. In addition, the book equips readers to easily develop the pathological brain detection system further on their own and apply the technologies to other research fields, such as Alzheimer's detection, multiple sclerosis detection, etc.
Dr. Shui-Hua Wang received her B.S. degree from Southeast University in 2008 and an M.S. from the City University of New York in 2012. She received her Ph.D. from Nanjing University in 2016. She is currently an assistant professor at Nanjing Normal University, and a visiting researcher in University of Leicester, UK. She serves as the editor of Journal of Alzheimer’s disease. In the past, she served as the guest lead editor of International Journal of Biomedical Imaging and Multimedia Tools and Application. Prof. Dr. Yu-Dong Zhang received his B.S. and M.S. degrees from Nanjing University of Aeronautics and Astronautics in 2004 and 2007. He received his Ph.D. degree in Signal and Information Processing from Southeast University in 2010. From 2010 to 2012, he worked at Columbia University as a postdoc. From 2012 to 2013, he worked as a research scientist at Columbia University and New York State Psychiatric Institute. From 2013 to 2017, he worked as a full professor and doctoral advisor at School of computer science and technology at Nanjing Normal University. From 2018, he is a full Professor in Department of Informatics, University of Leicester, UK. His research interests include biomedical image processing, pattern recognition, and artificial intelligence. Prof. Dr. Zhengchao Dong is a former Associate Professor of Translational Imaging at Columbia University, USA. Having also served at New York State Psychiatry Institute, USA, he has published over 20 papers on JAMA Psychiatry, Progress in Nuclear Magnetic Resonance Spectroscopy, Neuropsychopharmacology, Neuroimages, Human Brain Mapping, etc. Preetha Phillips is currently pursuing her Doctor of Osteopathic Medicine degree at West Virginia School of Osteopathic Medicine. She received her B.S. degree from Shepherd University in May 2016. She has conducted research on using magnetic resonance spectroscopy (MRS) to diagnose panic disorder, and on the analysis of pain mechanisms in rats.
1 Basics of Pathological Brain Detection (PBD).- 2 Neuroimaging Modalities: Strengths and Weaknesses.- 3 Image Preprocessing for Pathological Brain Detection: A Summary.- 4 Canonical Feature Extraction Methods for Structural Magnetic Resonance Imaging.- 5 Multi-scale and Multi-resolution Features for Structural Magnetic Resonance Imaging.- 6 Dimensionality Reduction of Brain Image Features.- 7 Classification Methods for Pathological Brain Detection.- 8 Weight Optimization of Classifiers for Pathological Brain Detection.- 9 Comparison of Current PBD Systems.
| Erscheint lt. Verlag | 20.7.2018 |
|---|---|
| Reihe/Serie | Brain Informatics and Health | Brain Informatics and Health |
| Zusatzinfo | XXVI, 214 p. |
| Verlagsort | Singapore |
| Sprache | englisch |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Medizin / Pharmazie ► Gesundheitsfachberufe | |
| Medizin / Pharmazie ► Medizinische Fachgebiete ► Neurologie | |
| Medizinische Fachgebiete ► Radiologie / Bildgebende Verfahren ► Radiologie | |
| Studium ► 2. Studienabschnitt (Klinik) ► Anamnese / Körperliche Untersuchung | |
| Schlagworte | Artificial Intelligence • Bioinspired Algorithm • Classifier • Deep learning • diagnostic radiology • Image Normalization • machine learning • Magnetic Resonance Imaging • Pathological brain detection • pattern recognition • Wavelet |
| ISBN-10 | 981-10-4026-5 / 9811040265 |
| ISBN-13 | 978-981-10-4026-9 / 9789811040269 |
| Haben Sie eine Frage zum Produkt? |
PDF (Wasserzeichen)Größe: 11,2 MB
DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasserzeichen und ist damit für Sie personalisiert. Bei einer missbräuchlichen Weitergabe des eBooks an Dritte ist eine Rückverfolgung an die Quelle möglich.
Dateiformat: PDF (Portable Document Format)
Mit einem festen Seitenlayout eignet sich die PDF besonders für Fachbücher mit Spalten, Tabellen und Abbildungen. Eine PDF kann auf fast allen Geräten angezeigt werden, ist aber für kleine Displays (Smartphone, eReader) nur eingeschränkt geeignet.
Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.
Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.
aus dem Bereich
