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A Brief Overview on Statistical Shape Analysis

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Permutation Tests in Shape Analysis

Part of the book series: SpringerBriefs in Statistics ((BRIEFSSTATIST,volume 15))

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Abstract

In this chapter we introduce the basic concepts and terms that will be used throughout the book. In particular we provide a brief overview of statistical shape analysis and geometric morphometric techniques, focussing on landmark and semilandmark-based representations of shapes.Shape is described as the geometric property of an object invariant under rotation, scale, or translation. Morphometric is a new promising branch of statistics that integrates knowledge from mathematics, geometry, biometrics, computer science, and modern engineering (essential especially for complicated three-dimensional object) to study shape and size of objects, along with their covariations with other variables. In this context the shape of an object is considered as a whole, align with the interdependence of its parts and conclusions are drawn under conditions of uncertainty. Geometric morphometrics is a more recent area of morphometrics that, by means of statistical tools, analyzes geometric information of objects, focusing on exactly where points or parts of the organism are located with respect to each other. To illustrate how landmarks and semilandmarks are chosen and then classified in real applications, we propose two case studies.

We have the duty of formulating, of summarizing, and of communicating our conclusions, in intelligible form, in recognition of the right of other free minds to utilize them in making their own decisions”.

Statistical methods and scientific induction. Journal of the Royal Statistical Society, B, 17, 69–78, 1955.

R.A. Fisher

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References

  • Adams DC (1999) Methods for shape analysis of landmark data from articulated structures. Evolutionary Ecology Research 1:959–970

    Google Scholar 

  • Adams DC, Rohlf FJ, Slice DE (2004) Geometric morphometrics: ten years of progress following the ‘revolution’. Italian Journal of Zoology 71:5–16

    Article  Google Scholar 

  • Bookstein FL (1978) The Measurement of Biological Shape and Shape change, volume 24 of Lecture notes on biomathematics. Springer-Verlag, New York

    Book  Google Scholar 

  • Bookstein FL (1986) Size and shape spaces for landmark data in two dimensions. Statistical Science 1:181–242

    Article  MATH  Google Scholar 

  • Bookstein FL (1989) Principal warps: Thin-plate splines and the decomposition of deformations. IEEE Trans. Pattern Anal. Machine Intell., 11:567–585

    Article  MATH  Google Scholar 

  • Bookstein FL (1991) Morphometric Tools For Landmark Data: Geometry and Biology. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  • Bookstein FL (1996) Combining the tools of geometric morphometrics. In: Advances in morphometrics, vol 284, Plenum Press, New York, pp 131–151

    Google Scholar 

  • Bookstein FL (1997) Shape and the information in medical images: A decade of the morphometric synthesis. Computer Vision and Image Understanding 66:97–118

    Article  Google Scholar 

  • Brombin C (2009) A nonparametric permutation approach to statistical shape analysis, ph.D. thesis. Padova, Italy: University of Padova

    Google Scholar 

  • Brombin C, Salmaso L (2009) Multi-aspect permutation tests in shape analysis with small sample size. Computational Statistics & Data Analysis 53:3921–3931

    Article  MathSciNet  MATH  Google Scholar 

  • Brombin C, Pesarin F, Salmaso L (2008) Dealing with more variables than sample sizes: an application to shape analysis. In: Hunter DR, Richards DSP, Rosenberger JL (eds) Nonparametric Statistics and Mixture Models: A Festschrift in Honor of Thomas P. Hettmansperger, Singapore: World Scientific, pp 28–44

    Google Scholar 

  • Brombin C, Mo G, Zotti A, Giurisato M, Salmaso L, Cozzi B (2009) A landmark analysis-based approach to age and sex classification of the skull of the mediterranean monk seal (monachus monachus) (hermann, 1779). Anatomia, Histologia, Embryologia 38:382–386

    Article  Google Scholar 

  • Brombin C, Salmaso L, Ferronato G, Galzignato P (2011) Multi-aspect procedures for paired data with application to biometric morphing. Communications in Statistics - Simulation and Computation 40:1–12

    Article  MathSciNet  MATH  Google Scholar 

  • Dryden IL, Mardia KV (1993) Multivariate Shape Analysis. Sankhyā Series A 55:460–480

    MathSciNet  MATH  Google Scholar 

  • Dryden IL, Mardia KV (1998) Statistical Shape Analysis. John Wiley & Sons, London

    MATH  Google Scholar 

  • Etöz A (2011) Anthropometric analysis of the nose. In: Brenner DM (ed) Rhinoplasty, InTech

    Google Scholar 

  • Farkas LG (1994) Anthropometry of the Head and Face. Raven Press, New York

    Google Scholar 

  • Farkas LG, Katic MJ, Forrest CR (2005) International anthropometric study of facial morphology in various ethnic groups/races. Journal of Craniofacial Surgery 16:615–646

    Article  Google Scholar 

  • Goodall CR (1991) Procrustes methods in the statistical analysis of shape. Journal of the Royal Statistical Society, Series B 53:285–339

    MathSciNet  MATH  Google Scholar 

  • Gower JC (1975) Generalized procrustes analysis. Psychometrika 40:33–50

    Article  MathSciNet  MATH  Google Scholar 

  • Huxley JS (1932) Problems of Relative Growth. The Dial Press, New York

    Google Scholar 

  • Katina S, Bookstein FL, Gunz P, Schaefer K (2007) What is worth digitizing all those curve? a worked example from craniofacial primatology. American Journal of Physical Anthropology, Abstracts of American Academy of Physician Assistants (AAPA) poster and podium presentations 132, S44:140

    Google Scholar 

  • Kendall DG (1977) The diffusion of shape. Advances in Applied Probability 9:428–430

    Article  Google Scholar 

  • Kendall DG (1984) Shape manifolds, Procrustean metrics, and complex projective spaces. Bulletin of the London Mathematical Society 16:81–121

    Article  MathSciNet  MATH  Google Scholar 

  • Kendall DG (1989) A survey of the statistical theory of shape. Statistical Science 4:87–120

    Article  MathSciNet  MATH  Google Scholar 

  • Kent JT (1994) The complex bingham distribution and shape analysis. Journal of the Royal Statistical Society: Series B 56:285–299

    MathSciNet  MATH  Google Scholar 

  • Kent JT (1995) Current issues for statistical inference in shape analysis. In: Mardia KV, Gill CA (eds) Proceedings inProceedings in Current Issues in Statistical Shape Analysis, University of Leeds, University of Leeds Press, pp 167–175

    Google Scholar 

  • Le H, Kendall DG (1993) The riemannian structure of euclidean shape spaces: a novel environment for statistics. Annals of Statistics 21:1225–1271

    Article  MathSciNet  MATH  Google Scholar 

  • Lele S, Richtsmeier JT (1991) Euclidean distance matrix analysis: a coordinate free approach for comparing biological shapes using landmark data. American Journal of Physical Anthropology 86:415–427

    Article  Google Scholar 

  • Lele SR, Richtsmeier JT (2001) An invariant approach to statistical analysis of shapes. Chapman & Hall/CRC, Boca Raton, Florida

    Book  MATH  Google Scholar 

  • Mardia KV (1995) Shape advances and future perspectives. In: Mardia KV, Gill CA (eds) Proceedings in Current Issues in Statistical Shape Analysis, University of Leeds, University of Leeds Press, pp 57–75

    Google Scholar 

  • Mardia KV, Dryden IL (1989) The statistical analysis of shape data. Biometrika 76:271–281

    Article  MathSciNet  MATH  Google Scholar 

  • Mardia KV, Edwards R, Puri ML (1977) Analysis of Central Place Theory. Bulletin of the International Statistical Institute 47:93–110

    MathSciNet  Google Scholar 

  • Mo G (2005) Anatomy of the skull of mediterranean monk seal, Monachus monachus, functional morphology, densitometry, morphometrics and notes on natural history. PhD thesis, University of Padova

    Google Scholar 

  • O’Higgins P (2000) The study of morphological variation in the hominid fossil record: biology, landmarks and geometry. Journal of Anatomy 197:103–120

    Article  Google Scholar 

  • Pesarin F (2001) Multivariate Permutation tests: with application in Biostatistics. John Wiley & Sons, Chichester-New York

    Google Scholar 

  • Pesarin F, Salmaso L (2010) Permutation Tests for Complex Data: Theory, Applications and Software. Wiley

    Book  Google Scholar 

  • Rao C, Suryawanshi S (1996) Statistical analysis of shape of objects based on landmark data. Proceedings of the National Academy of Sciences of the United States of America 93:12132–12136

    Article  MATH  Google Scholar 

  • Rao C, Suryawanshi S (1998) Statistical analysis of shape through triangulation of landmarks: a study of sexual dimorphism in hominids. Proceedings of the National Academy of Sciences of the United States of America 95:4121–4125

    Article  MathSciNet  MATH  Google Scholar 

  • Rasband W (1997–2012) ImageJ. U. S. National Institutes of Health, Bethesda, Maryland, USA, State University of New York at Stony Brook, http://imagej.nih.gov/ij/

  • Rohlf FJ (1999) Shape statistics: Procrustes superimpositions and tangent spaces. Journal of Classification 16:197–225

    Article  MATH  Google Scholar 

  • Rohlf FJ (2007) tpsDig2, digitize landmarks and outlines, version 2.12. Department of Ecology and Evolution, State University of New York at Stony Brook

    Google Scholar 

  • Rohlf FJ (2008) tpsRelw, Relative warps analysis, version 1.46. Department of Ecology and Evolution, State University of New York at Stony Brook

    Google Scholar 

  • Rohlf FJ, Slice DE (1990) Extensions of the procrustes method for the optimal superimposition of landmarks. Systematic Zoolology 39:40–59

    Article  Google Scholar 

  • Schneider C, Rasband W, Eliceiri K (2012) Nih image to imagej: 25 years of image analysis. Nature Methods 9:671–675

    Article  Google Scholar 

  • Siegel AF, Benson RH (1982) A robust comparison of biological shapes. Biometrics 38:341–350

    Article  MATH  Google Scholar 

  • Slice DE (2005) Modern Morphometrics In Physical Anthropology. Springer-Verlag New York, LLC

    Book  Google Scholar 

  • Slice DE, Bookstein FL, Marcus LF, Rohlf FJ (1996) A glossary for geometric morphometrics. Advances in Morphometrics 284:531–551

    Google Scholar 

  • Small CG (1988) Techniques of shape analysis on sets of points. International Statistical Review 56:243–257

    Article  MATH  Google Scholar 

  • Small CG (1996) The Statistical Theory of Shape. Springer, New York

    Book  MATH  Google Scholar 

  • Spoor F, Jefferies N, Zonneveld F (2000) Imaging skeletal growth and evolution. In: O’Higgins P, Cohn MJ (eds) Development, Growth and Evolution: Implications for the Study of the Hominid Skeleton, London: Academic Press, pp 123–161

    Google Scholar 

  • Srivastava A, Joshi S, Mio W, Liu X (2005) Statistical shape analysis: Clustering, learning and testing. IEEE Transactions on Pattern Analysis and Machine Intelligence 27:590–602

    Article  Google Scholar 

  • Stoyan D, Stoyan H (1994) Fractals, Random Shapes and Point Fields: Methods of geometric statistics. Wiley, Chichester

    MATH  Google Scholar 

  • Stoyan D, Kendall WS, Mecke J (1995) Stochastic geometry and its applications, 2nd Edition. Wiley, Chichester, England

    MATH  Google Scholar 

  • Thompson DW (1961) On Growth and Form. University Press, Cambridge

    Google Scholar 

  • Weber GW, Bookstein FL (2011) Virtual Anthropology: a guide to a new interdisciplinary field. Springer: New York

    Book  Google Scholar 

Download references

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Brombin, C., Salmaso, L. (2013). A Brief Overview on Statistical Shape Analysis. In: Permutation Tests in Shape Analysis. SpringerBriefs in Statistics, vol 15. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8163-8_1

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