Buch, Englisch, Band 18, 150 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 289 g
From Glymphatics to Deep Learning
Buch, Englisch, Band 18, 150 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 289 g
Reihe: Simula SpringerBriefs on Computing
ISBN: 978-3-032-00678-3
Verlag: Springer
This open access book revolves around predictive mathematical modelling and simulation of brain multiphysics with an emphasis on cerebrospinal fluid flow and solute transport in and around the human brain. The book consists of 10 self-contained and relatively short chapters, each offering a rapid introduction to a key problem or topic, supported by open source software. Readers will gain insights into state-of-the-art mathematical tools and techniques for modelling and simulation of brain multiphysics ranging from classical finite element approaches, network-based modelling techniques and deep neural networks. The target audiences are researchers in applied mathematics, scientific computing, biophysics, bioengineering or computational neuroscience interested in a compact introduction to image-based computational modeling of brain multiphysics and cutting-edge available tools.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Naturwissenschaften Physik Physik Allgemein Theoretische Physik, Mathematische Physik, Computerphysik
- Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Neurowissenschaften, Kognitionswissenschaft
- Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Chirurgie Neurochirurgie
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
Weitere Infos & Material
1 From brain physiology to brain physics.- 2 Meshing the intracranial compartments: Cerebellum, cerebrum, brainstem and cerebrospinal fluid.- 3 Segmenting, meshing and modeling CSF spaces.- 4 The pulsating brain: An interface-coupled fluid-poroelasticinteraction model of the cranial cavity.- 5 Quantifying cerebrospinal fluid tracer concentration in the brain.- 6 Signal increase ratio prediction with CNNs.- 7 Estimating molecular transport parameters using inverse PDEmodels.- 8 Two-compartment modeling of tracer transport in the brain.- 9 An introduction to identifying velocity fields from contrast imaging via PDE-constrained optimization. 10 An introduction to network models of neurodegenerative diseases.
