Research and innovation

The new face of statistics

Issued: Mon, 04 Jul 2011 11:21:00 BST

An interdisciplinary project, which focuses on children born with cleft lip and palate, has brought together the diverse expertise of the University to develop a three-dimensional facial modeling system that can be used to collect and analyse data, to quantify how surgical procedures for this kind of condition affect facial growth and structure.

The new face of statistics Professor of Statistics Adrian Bowman explains how the data capture system, developed by computing scientists at the University and now available through a spin-out company, works: ‘The stereo camera system uses a pair of cameras set up at different viewing positions which each take a slightly different photograph of the child’s face. The two images can then be matched and stereo-photogrammetry used to work out how far away things are. Essentially the camera mimics the way our brains work when we look at an object and the end result is a computerised 3D image.’

Both children born with and without a cleft lip have been studied so that Professor Bowman and his team can develop statistical methods of analysing how the faces of post-surgery children grow. The team have been exploring anatomical landmarks, or key positions on the 3D images, to measure the asymmetrical discrepancies between pre- and post-surgery cleft cases against cases without cleft lip. ‘In a cleft case there is a much higher degree of asymmetry but after surgery the asymmetry score drops. However, it is still markedly higher than non-cleft cases.’

Professor Bowman continues: ‘It’s difficult to get data because you have to record the child year after year and we’ve managed to do that with some of our studies. So we’re now beginning to build up a picture of how the face grows over the early years of life. Our work is essentially an audit of what actually happens when these operations take place and what unusual features might still be left with the child, which could be informative for later surgery.’

Professor Bowman has been keen to use the skills of his research students to progress the project and find innovative ways of improving the quality of data obtainable through 3D facial modelling: ‘One of our research students looked at curvature around the top lip, across the nose and along the profile of the images. Curves offer a richer set of information than simple points. While it is true to say that methods for shape analysis have been around for a while, they have usually been based on landmark single point representations of the face. However, trying to model the face as a whole, as we are doing, is state of the art.’

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