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Computational Neuroanatomy Using Deformable Neuroanatomical Models: Applications in Brain Imaging

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Computational Methods in Biophysics, Biomaterials, Biotechnology and Medical Systems

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18.1 2.1 Computational Models for Neuroanatomy

The advent of tomographic imaging such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), ultrasound (US), and others, has given scientists and clinicians the opportunity to look at the structure and the function of the human brain in vivo. The concomitant development of computerized image analysis methods and algorithms, during the past 15 years, has made it possible to quantitatively analyze data obtained via any of these tomographic imaging methods. Moreover, as more and more emphasis is placed on the automation of these methods, the possibility to perform studies including hundreds, or even thousands of subjects is becoming more tangible. The capability to process large amounts of data is very important, since it increases the statistical power of such studies, i.e. their ability to detect subtle effects of age, gender, disease, or other factors on the anatomy or the physiology of the...

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Authors
  1. Cornelius T. Leondes
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Cornelius T. Leondes

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Leondes, C.T. (2003). Computational Neuroanatomy Using Deformable Neuroanatomical Models: Applications in Brain Imaging. In: Leondes, C.T. (eds) Computational Methods in Biophysics, Biomaterials, Biotechnology and Medical Systems. Springer, Boston, MA. https://doi.org/10.1007/0-306-48329-7_18

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  • DOI: https://doi.org/10.1007/0-306-48329-7_18

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-7110-2

  • Online ISBN: 978-0-306-48329-5

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