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The Fractal Geometry of the Brain

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	The Fractal Geometry of the Brain/ edited by Antonio Di Ieva.
其他作者:	Di Ieva, Antonio.
面頁冊數:	XXII, 585 p. 175 illus., 86 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Neurosciences. -
電子資源:	https://doi.org/10.1007/978-1-4939-3995-4
ISBN:	9781493939954

The Fractal Geometry of the Brain
The Fractal Geometry of the Brain[electronic resource] /edited by Antonio Di Ieva. - 1st ed. 2016. - XXII, 585 p. 175 illus., 86 illus. in color.online resource. - Springer Series in Computational Neuroscience,2197-1900. - Springer Series in Computational Neuroscience,14.

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 Studies of 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.

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.

ISBN: 9781493939954

Standard No.: 10.1007/978-1-4939-3995-4doiSubjects--Topical Terms:

593561
Neurosciences.

LC Class. No.: RC321-580

Dewey Class. No.: 612.8

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