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Department of Engineering |
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F-AHG-1: Medical imaging and 3D computer graphics - registration of
the human femur
This project should appeal to 3G4 students, since it encompasses
medical imaging (CT), shape analysis and graphical rendering. The
motivation is to establish how structural properties of an
individual's femur might predispose that person to hip fracture. This
is a hugely important health and wealth issue: hip fracture amongst
the elderly causes significant physical and emotional distress, and
the cost to health services is considerable, with annual cases
forecast to rise to 6.3 million worldwide by 2050. High risk
individuals could receive targeted therapy (drugs, exercise), but
current screening methods fail to spot the majority of individuals who
go on to fracture.
Our recent pioneering
research demonstrates the power of cortical thickness
maps. These are coloured renderings of the bone surface that show
the thickness of the stiff, outer shell (cortex) which is responsible
for most of the bone's strength. However, in order to answer the
important questions (what type of cortical thickness distribution
might predispose an individual to fracture, does any particular
therapy increase cortical thickness in the right regions?) it is
necessary to compare cortical thickness maps across many
individuals. And before we can compare one individual with another, we
must first register (spatially align) their cortical thickness
maps.
Registration is a key topic in medical imaging research, and we
have already implemented an algorithm that does an excellent job of
aligning two femur surfaces using a global affine transformation
followed by a nonrigid B-spline free-form deformation. What is less clear is
how well the technique aligns corresponding landmarks on the two
surfaces: just because the surfaces align closely, it does not
necessarily follow that point A on surface 1 aligns with the
corresponding point A on surface 2. This project will investigate a
range of alternative registration algorithms and assess their
performance with regards to landmark alignment.
The project will be supported by data and advice from the Bone
Research Group at Addenbrooke's Hospital.
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Our recent research has shown how to extract cortical thickness maps
(top right, pink is thin, blue is thick) from CT data (top
left) by deconvolution (bottom). The result is a detailed, accurate
map of an individual bone. |
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For cohort studies, we need to register individual femurs onto a
common morphology. We currently do this using a global affine
transformation (left, first nine frames) followed by a nonrigid
B-spline free-form deformation (left, last eight frames). While this
aligns the surfaces nicely, it is not clear whether we are optimally
aligning corresponding landmarks on the surfaces. |
