Anatomical curve identification

Bowman, A. W. , Katina, S., Smith, J. and Brown, D. (2015) Anatomical curve identification. Computational Statistics and Data Analysis, 86, pp. 52-64. (doi: 10.1016/j.csda.2014.12.007) (PMID:26041943) (PMCID:PMC4394146)

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Methods for capturing images in three dimensions are now widely available, with stereo-photogrammetry and laser scanning being two common approaches. In anatomical studies, a number of landmarks are usually identified manually from each of these images and these form the basis of subsequent statistical analysis. However, landmarks express only a very small proportion of the information available from the images. Anatomically defined curves have the advantage of providing a much richer expression of shape. This is explored in the context of identifying the boundary of breasts from an image of the female torso and the boundary of the lips from a facial image. The curves of interest are characterised by ridges or valleys. Key issues in estimation are the ability to navigate across the anatomical surface in three-dimensions, the ability to recognise the relevant boundary and the need to assess the evidence for the presence of the surface feature of interest. The first issue is addressed by the use of principal curves, as an extension of principal components, the second by suitable assessment of curvature and the third by change-point detection. P-spline smoothing is used as an integral part of the methods but adaptations are made to the specific anatomical features of interest. After estimation of the boundary curves, the intermediate surfaces of the anatomical feature of interest can be characterised by surface interpolation. This allows shape variation to be explored using standard methods such as principal components. These tools are applied to a collection of images of women where one breast has been reconstructed after mastectomy and where interest lies in shape differences between the reconstructed and unreconstructed breasts. They are also applied to a collection of lip images where possible differences in shape between males and females are of interest.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Katina, Dr Stanislav and Smith, Miss Joanna and Bowman, Prof Adrian and Brown, Dr Denise
Authors: Bowman, A. W., Katina, S., Smith, J., and Brown, D.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Computational Statistics and Data Analysis
Publisher:Elsevier B.V.
ISSN (Online):1872-7352
Copyright Holders:Copyright © 2014 The Authors
First Published:First published in Computational Statistics and Data Analysis 86:52-64
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
477842The analysis of three-dimensional facial dysmorphologyAdrian BowmanWellcome Trust (WELLCOME)086901/Z/08/ZM&S - STATISTICS
5006112008-12 Doctoral Training GrantMary GoodmanEngineering & Physical Sciences Research Council (EPSRC)EP/P50418X/1VICE PRINCIPAL RESEARCH & ENTERPRISE
5006132008-12 Doctoral Training GrantMary GoodmanEngineering & Physical Sciences Research Council (EPSRC)EP/P50418X/1VICE PRINCIPAL RESEARCH & ENTERPRISE
474861Wellcome Trust VIP Awards 2008-2009John CogginsWellcome Trust (WELLCOME)084546/Z/07/ZPRO-VICE PRINCIPAL
500261Wellcome VIP awardSarah CleavelandWellcome Trust (WELLCOME)084546/Z/07/ZRI BIODIVERSITY ANIMAL HEALTH & COMPMED