Bi8773 Practicals in shape analysis I

Faculty of Science
Autumn 2024
Extent and Intensity
0/2/0. 2 credit(s). Type of Completion: z (credit).
Taught in person.
Teacher(s)
doc. RNDr. Miroslav Králík, Ph.D. (lecturer)
Mgr. Karolína Kupková (seminar tutor)
Guaranteed by
doc. RNDr. Miroslav Králík, Ph.D.
Department of Anthropology – Biology Section – Faculty of Science
Contact Person: doc. RNDr. Miroslav Králík, Ph.D.
Supplier department: Department of Anthropology – Biology Section – Faculty of Science
Prerequisites
Basic knowledge of applied statistics and R programming, prerequisites MAS01 and MaS02.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The aim of this course is to acquaint students with methods of traditional and geometric morphometry in anthropology and to practice students in collecting morphometric data and in basics of morphometric analysis in freely available morphometric programs.
Learning outcomes
At the end of this course the students should be able to:
understand and explain basic principles of traditional and geometric morphometrics (shape analysis), perform manual and (semi)automatic identification of anatomical landmarks, curves, and surfaces on the biological objects;
understand multivariate statistical methods for EEG, ECG, and morphometric data (multivariate SVD models, multivariate splines, multivariate regression, functional and Fourier models);
interpret 2D/3D statistical visualisation.
Syllabus
  • Theoretical part (lecture)
  • 1. Nature of biological form: form, size, shape, adaptive and non-adaptive nature of the form.
  • 2. Method of recording shape and size: dimensions, angles, landmarks, curves, surfaces, the importance of homology and its securing, types of homology.
  • 3. Methods of form comparison and form analysis: traditional and modern morphometrics, geometric morphometrics (GM), traditional dimensional morphometrics, traditional morphometrics on 2D objects, automatic size/shape measurements in image analysis programs.
  • 4. Geometric morphometryics, basic procedures of superposition of landmark configurations, shape spaces, consequences for shape variables, visualization of shape differences.
  • 5. Other methods of modern morphometrics: methods of sliding semilandmarks, semilandmarks in 2D surface; analysis of outlines (curves), Fourier analysis, elliptic Fourier analysis, wavelet analysis, functional data analysis (FDA) of curves.
  • 6. Analysis of shape differences and relations of shape with external factors on population level, testing of shape differences, methods of multivariate statistics in geometric morphometrics.
  • Practical part (exercises in the form of data preparation and analysis on student´s own computer)
  • 7. Collecting (digitizing) 2D coordinates in TPS programs (tpsDig2, tpsUtil).
  • 8. Obtaining contours in tpsDig2, automatic measurement of objects in ImageJ.
  • 9. Measurement of 3D coordinates in software Landmark, R (geomorph package) and Meshlab.
  • 10. Shape analysis of 2D coordinate configurations in TPS and PAST programs.
  • 11. Morphometric data loading and manipulations, basic shape analysis in R-software (packages: shapes, geomorph).
  • 12. Preparation / completion of measurement of own 2D and 3D data (for acquiring credits).
Literature
    recommended literature
  • DRYDEN, I. L. and K. V. MARDIA. Statistical shape analysis. Chichester: John Wiley & Sons. xvii, 347. ISBN 0471958166. 1998. info
Teaching methods
Class lecture and excercise, homework.
Assessment methods
Assessment at the end of the semester will take the form of a credit on the basis of a written protocol on the practical tasks performed.
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught: every week.
The course is also listed under the following terms Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, autumn 2021, Autumn 2022, Autumn 2023.
  • Enrolment Statistics (Autumn 2024, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2024/Bi8773