|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab > Medical Imaging Group|
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|The thickness of the cortex (outer bone surface) can be measured at lots of locations over the femoral head: this is crucial information for determining risk of fracture.||These measurement locations are at the vertices of a polygonal mesh which covers the femoral surface. The mesh is created manually - it only represents the approximate location of the surface.||The thickness estimation process can also calculate exactly where the outer and inner cortical surfaces should really be. However, though many of the measurements are very good, some are not.||The erroneous measurements look obvious from these pictures (the spikes on the surface): can they be automatically removed and replaced with correct measurements to generate a much better mesh?|
Hip fracture is a major issue affecting millions of people annually. Hip fracture risk is mainly related to the strength and thickness of the denser layer of cortical bone surrounding the cancellous bone in the centre. It is known that this layer of bone can become thinner with increasing age, particularly in regions of the femur which are often involved in fracture due to a fall.
We have recently developed a technique which can accurately estimate cortical thickness and map it to a 3D computer surface of the hip. We have been using this across large patient cohorts to try to work out which bits of the cortical layer have different thickness in different circumstances. However, it is also clinically important to determine whether such changes are at the outer (periosteal) or inner (endocortical) surfaces of the cortex. Equally, knowing exactly where these surfaces are allows more detailed FEM (mechanical) analysis of the hip. The thickness technique is based on an approximate manual segmentation, but it does calculate, for each vertex in the segmentation, how far away each of the cortical surfaces really are. So the manual segmentation can be adjusted by these values to generate inner and outer surfaces. But these surfaces are noisy in some places and not terribly useful at present.
This project will investigate how to remove such noise. There are several completely different approaches that might be taken to do this. We could start with the adjusted mesh and try to find a way to reliably spot 'outliers'. Or we could make use of the estimated reliability of each estimate and construct some form of filter using this. Or we could go back to the thickness estimation technique itself, and try to use neighbouring (presumably good) results to try to force the algorithm to pick surface locations which are realistic.
This is an algorithmic development / computational geometry / software project, so experience of writing software is essential, though the development could also be done using Matlab. The project involves some collaboration with the bone research group at Addenbrooke's Hospital.
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