Shape curve analysis using curvature

Miller, James (2009) Shape curve analysis using curvature. PhD thesis, University of Glasgow.

Abstract

Statistical shape analysis is a field for which there is growing demand. One of the major drivers for this growth is the number of practical applications which can use statistical shape analysis to provide useful insight. An example of one of these practical applications is investigating and comparing facial shapes. An ever improving suite of digital imaging technology can capture data on the three-dimensional shape of facial features from standard images. A field for which this offers a large amount of potential analytical benefit is the reconstruction of the facial surface of children born with a cleft lip or a cleft lip and palate. This thesis will present two potential methods for analysing data on the facial shape of children who were born with a cleft lip and/or palate using data from two separate studies. One form of analysis will compare the facial shape of one year old children born with a cleft lip and/or palate with the facial shape of control children. The second form of analysis will look for relationships between facial shape and psychological score for ten year old children born with a cleft lip and/or palate. While many of the techniques in this thesis could be extended to different
applications much of the work is carried out with the express intention of producing meaningful analysis of the cleft children studies.

Shape data can be defined as the information remaining to describe the shape of an object after removing the effects of location, rotation and scale. There are numerous techniques in the literature to remove the effects of location, rotation and scale and thereby define and compare the shapes of objects. A method which does not require the removal of the effects of location and rotation is to define the shape according to the bending of
important shape curves. This method can naturally provide a
technique for investigating facial shape. When considering a child's face there are a number of curves which outline the important features of the face. Describing these feature curves gives a large amount of information on the shape of the face.

This thesis looks to define the shape of children's faces using functions of bending, called curvature functions, of important feature curves. These curvature functions are not only of use to define an object, they are apt for use in the comparison of two or more objects. Methods to produce curvature functions which provide an accurate description of the bending of face curves will be introduced in this thesis. Furthermore, methods to compare the facial shape of groups of children will be discussed. These methods will be used to compare the facial shape of children with a cleft lip and/or palate with control children.

There is much recent literature in the area of functional
regression where a scalar response can be related to a functional predictor. A novel approach for relating shape to a scalar response using functional regression, with curvature functions as predictors, is discussed and illustrated by a study into the psychological state of ten year old children who were born with a cleft lip or a cleft lip and palate. The aim of this example is to investigate whether any relationship exists between the bending of facial features and the psychological score of the children, and where relationships exist to describe their nature.

The thesis consists of four parts. Chapters 1 and 2 introduce the data and give some background to the statistical techniques. Specifically, Chapter 1 briefly introduces the idea of shape and how the shape of objects can be defined using curvature. Furthermore, the two studies into facial shape are introduced which form the basis of the work in this thesis. Chapter 2 gives a broad overview of some standard shape analysis techniques, including Procrustes methods for alignment of objects, and gives further details of methods based on curvature. Functional data analysis techniques which are of use throughout the thesis are also discussed.

Part 2 consists of Chapters 3 to 5 which describe methods to find curvature functions that define the shape of important curves on the face and compare these functions to investigate differences between control children and children born with a cleft lip and/or palate. Chapter 3 considers the issues with finding and further analysing the curvature functions of a plane curve whilst Chapter 4 extends the methods to space curves. A method which projects a space curve onto two perpendicular planes
and then uses the techniques of Chapter 3 to calculate curvature is introduced to facilitate anatomical interpretation. Whilst the midline profile of a control child is used to illustrate the methods in Chapters 3 and 4, Chapter 5 uses curvature functions to investigate differences between control children and children born with a cleft lip and/or palate in terms of the bending of their upper lips.

Part 3 consists of Chapters 6 and 7 which introduce functional regression techniques and use these to investigate potential relationships between the psychological score and facial shape, defined by
curvature functions, of cleft children. Methods to both display graphically and formally analyse the regression procedure are discussed in Chapter 6 whilst Chapter 7 uses these methods to provide a systematic analysis of any relationship between psychological score and facial shape.

The final part of the thesis presents conclusions discussing both the effectiveness of the methods and some brief anatomical/psychological findings. There are also suggestions of potential future work in the area.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Keywords: Cleft Impairment, Curvature, Functional Regression, Functional Data Analysis
• Subjects: Q Science > QA Mathematics
• Colleges/Schools: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• Supervisor's Name: Bowman, Professor Adrian W
• Date of Award: 2009
• Depositing User: Mr James Miller
• Unique ID: glathesis:2009-854
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 08 Jun 2009
• Last Modified: 10 Dec 2012 13:27
• URI: https://theses.gla.ac.uk/id/eprint/854