Udemy

Practical Morphometrics Analysis (3D Model)

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  • 2,214 Students
  • Updated 2/2020
4.2
(23 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
3 Hour(s) 47 Minute(s)
Language
English
Taught by
Olalekan Agbolade
Rating
4.2
(23 Ratings)
3 views

Course Overview

Practical Morphometrics Analysis (3D Model)

A step-by-step approach to morphometrics based on three-dimensional images

Morphometrics has experienced a major revolution through the invention of coordinate-based methods, the discovery of the statistical theory of shape, and the computational realization of deformation grids. The ubiquitous application of fast personal computers and modern analytical tools have ushered in a new era of data analysis, permitting the exploration and visualization of large high-dimensional data sets along with exact statistical tests based on resampling procedures. This new morphometric approach has been termed geometric morphometrics as it preserves the geometry of the landmark configurations throughout the analysis and thus permits to represent statistical results as actual shapes or forms. Therefore, these lectures aim at teaching practically, the concept of statistical shape analysis from 3D images. To encourage learning by exploration; images, annotations and data reports from the hand study are made available for download.

Course Content

  • 4 section(s)
  • 22 lecture(s)
  • Section 1 Introduction
  • Section 2 Landmark and Acquisition in 3D
  • Section 3 Visualizing 3D Landmarks
  • Section 4 Statistical Analysis on 3D Landmark Data

What You’ll Learn

  • Introduction to morphometrics covering definitions, traditional morphometrics and geometric morphometrics, Landmarks and acqusition tools covering landmark types (anatomical or biological, mathematical, pseudo-landmarks), landmark homology, landmark acquisition tools and how to use, and error assessment with Procrustes ANOVA, Landmarks Visualization covering General Procrustes Analysis (GPA), visualization tools, scatter plots of landmark coordinates, Principal Component Analysis (PCA), Statistical methods and Analysis covering ANOVA, MANOVA, ANOSIM/PERMANOVA, regression & allometry, discriminant analysis and canonical variates analysis, clustering, EDMA


Reviews

  • S
    Srikant Natarajan
    5.0

    Excellent compilation. We had started a similar research and had lot of trouble understanding and assimilating. Dr. Olelakan has got the information spoton as required.

  • R
    Roy Minden Farman
    5.0

    Very clear and easy to follow along. Amazing job!

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