The Fractal Geometry of the Brain
1st Edition
Published on 3. August 2016
XXII, 585 pages
978-1-4939-3995-4 (ISBN)
Description
Reviews the most intriguing applications of fractal analysis in neuroscience with a focus on current and future potential, limits, advantages, and disadvantages. Will bring an understanding of fractals to clinicians and researchers also if they do not have a mathematical background, and will serve as a good tool for teaching the translational applications of computational models to students and scholars of different disciplines. This comprehensive collection is organized in four parts: (1) Basics of fractal analysis; (2) Applications of fractals to the basic neurosciences; (3) Applications of fractals to the clinical neurosciences; (4) Analysis software, modeling and methodology.
Reviews / Votes
"This is a text about computer and mathematical modeling of basic and clinical Neurological Sciences. . Brain modelers would be interested in this book." (Joseph Grenier, Amazon.com, June, 2018)More details
Series
Language
English
Place of publication
New York
United States
Publishing group
Springer US
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XXII, 585 p. 175 illus., 86 illus. in color.
File size
25,56 MB
ISBN-13
978-1-4939-3995-4 (9781493939954)
DOI
10.1007/978-1-4939-3995-4
Schweitzer Classification
Other editions
Additional editions
Antonio Di Ieva
The Fractal Geometry of the Brain
Book
08/2016
1st Edition
Springer
€246.09
Article exhausted; check for reprint
Content
Part I. Introduction to Fractal Geometry and its Applications to Neurosciences.- The Fractal Geometry of the Brain: An Overview.- 2. Box-Counting Fractal Analysis: A Primer for the Clinician.- Tenets and Methods of Fractal Analysis (1/f noise).- 4. Tenets, Methods and Applications of Multifractal Analysis in Neurosciences.- Part II. Fractals in Neuroanatomy and Basic Neurosciences.- Fractals in Neuroanatomy and Basic Neurosciences: An Overview.- Morphology and Fractal-Based Classifications of Neurons and Microglia.- The Morphology of the Brain Neurons: Box-counting Method in Quantitative Analysis of 2D Image.- Neuronal Fractal Dynamics.- Does a Self-Similarity Logic Shape the Organization of the Nervous System?.- Fractality of Cranial Sutures.- The Fractal Geometry of the Human Brain: An Evolutionary Perspective.- Part III. Fractals in Clinical Neurosciences.- Fractal Analysis in Clinical Neurosciences: An Overview.- Fractal Analysis in Neurological Diseases.- Fractal Dimension Studiesof the Brain Shape in Aging and Neurodegenerative Diseases.- Fractal Analysis in Neurodegenerative Diseases.- Fractal Analysis of the Cerebrovascular System Physiopathology.- Fractal and Chaos in the Hemodynamics of Intracranial Aneurysms.- Fractal-based Analysis of Arteriovenous Malformations (AVMs).- Fractals in Neuroimaging.- Computational Fractal-Based Analysis of MR Susceptibility Weighted Imaging (SWI) in Neuro-oncology and neurotraumatology.- Texture Estimation for Abnormal Tissue Segmentation in Brain MRI.- Tumor Growth in the Brain: Complexity and Fractality.- Histological Fractal-based Classification of Brain Tumors.- Computational Fractal-based Analysis of the Brain Tumors Microvascular Networks.- Fractal analysis of electroencephalographic time-series (EEG-signals).- On Multiscaling of Parkinsonian Rest Tremor Signals and Their Classification.- Fractals and Electromyograms.- Fractal analysis in Neuro-ophthalmology.- Fractals in Affective and Anxiety Disorders.-Fractal Fluency: An Intimate Relationship Between the Brain and Processing of Fractal Stimuli.- Part IV. Computational Fractal-Based Neurosciences.- Computational Fractal-based Neurosciences: An Overview.- ImageJ in Computational Fractal-based Neuroscience: Pattern Extraction and Translational Research.- Fractal Analysis in MATLAB: A Tutorial for Neuroscientists.- Methodology to Increase the Computational Speed to Obtain the Fractal Dimension Using GPU Programming.- Fractal Electronics as a Generic Interface to Neurons.- Fractal Geometry meets Computational Intelligence: Future Perspectives
