Computed tomography morphometry

  • What are the different types of morphometry?

    Two conceptually and statistically separate approaches are: (1) landmark-based morphometrics, using the relative position of a few anatomical landmarks, and (2) outline-based morphometrics,3,4 which captures the contour of forms through a sequence of close pseudo-landmarks..

  • What do you mean by morphometry?

    Morphometrics is derived from a Greek word morphe , “shape, form,” metria , “measurement.” Morphometry refers to the quantitative analysis of form, a concept that includes size and shape.
    Recent Advances and Neural Connectivity in Autism..

  • What is morphometric analysis mainly used for?

    Morphometric analyses are commonly performed on organisms, and are useful in analyzing their fossil record, the impact of mutations on shape, developmental changes in form, covariances between ecological factors and shape, as well for estimating quantitative-genetic parameters of shape..

  • Morphometry, or quantitative morphology, is a sensitive technique that can be of great value in evaluating alveolar epithelial changes caused by toxic substances, in particular when the injuries are localized or subtle.
Feb 29, 2020Conclusions. CT-based morphometric analysis of the odontoid is necessary before using 2-screw fixation technique. Single 4.5-mm Herbert screws 
Feb 29, 2020PATIENTS AND METHODOLOGYStep 1: The image is first centered and positioned such that it is passing through the midline in all 3 (axial, 
May 2, 2020Computerized tomography (CT) scan can replace older conventional radiography techniques by providing more accurate morphometric measurements.
Brain morphometry is a subfield of both morphometry and the brain sciences, concerned with the measurement of brain structures and changes thereof during development, aging, learning, disease and evolution.
Since autopsy-like dissection is generally impossible on living brains, brain morphometry starts with noninvasive neuroimaging data, typically obtained from magnetic resonance imaging (MRI).
These data are born digital, which allows researchers to analyze the brain images further by using advanced mathematical and statistical methods such as shape quantification or multivariate analysis.
This allows researchers to quantify anatomical features of the brain in terms of shape, mass, volume, and to derive more specific information, such as the encephalization quotient, grey matter density and white matter connectivity, gyrification, cortical thickness, or the amount of cerebrospinal fluid.
These variables can then be mapped within the brain volume or on the brain surface, providing a convenient way to assess their pattern and extent over time, across individuals or even between different biological species.
The field is rapidly evolving along with neuroimaging techniques—which deliver the underlying data—but also develops in part independently from them, as part of the emerging field of neuroinformatics, which is concerned with developing and adapting algorithms to analyze those data.

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