Mathematical Modeling of the Human Brain: From Magnetic Resonance Images to Finite Element Simulation

Author:   Kent-André Mardal ,  Marie E. Rognes ,  Travis B. Thompson ,  Lars Magnus Valnes
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2022
Volume:   10
ISBN:  

9783030951351


Pages:   118
Publication Date:   26 February 2022
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Mathematical Modeling of the Human Brain: From Magnetic Resonance Images to Finite Element Simulation


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Author:   Kent-André Mardal ,  Marie E. Rognes ,  Travis B. Thompson ,  Lars Magnus Valnes
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2022
Volume:   10
Weight:   0.221kg
ISBN:  

9783030951351


ISBN 10:   3030951359
Pages:   118
Publication Date:   26 February 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Introduction.- Working with magnetic resonance images of the brain.- From T1 images to numerical simulation.- Introducing heterogeneities.- Introducing directionality with diffusion tensors.- Simulating anisotropic diffusion in heterogeneous brain regions.- Concluding remarks and outlook.- References.- Index.

Reviews

The book represents an excellent introduction and hands-on guide to this important and exciting field, for applied mathematicians and image processing practitioners ... . It is, perhaps, most beneficial, to electrical and computer science majors who wish to rapidly immerse themselves in the field, in a manner that is mathematically correct and sound, yet also practical. (Emil Saucan, zbMATH 1501.92001, 2023)


“The book represents an excellent introduction and hands-on guide to this important and exciting field, for applied mathematicians and image processing practitioners … . It is, perhaps, most beneficial, to electrical and computer science majors who wish to rapidly immerse themselves in the field, in a manner that is mathematically correct and sound, yet also practical.” (Emil Saucan, zbMATH 1501.92001, 2023)


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