Abstract #3939
A robust automated multi-modality registration tool applied to abdominal aortic aneurysm
Chengjia Wang 1,2 , Georgia Koutraki 1,3 , Olivia Mcbride 3 , Alex Vesey 3 , Tom MacGillivray 1 , Calum Gray 1 , David Newby 1,3 , Keith Goatman 2 , and Scott Semple 1,3
1
Clinical Research Imaging Centre, University
of Edinburgh, Edinburgh, United Kingdom,
2
Toshiba
Medical Visualization System-Europe, Edinburgh, United
Kingdom,
3
Centre
for Cardiovascular Science, University of Edinburgh,
Edinburgh, United Kingdom
Combining multi-modality data is a challenging but
important step in the development of non-invasive
assessment of cardiovascular disease. We present a
semi-automatic scheme for inter-parameter and
inter-modality registration of aortic MR and CT data,
requiring only simple interactions. The algorithm was
evaluated in a clinical trial investigating the
diagnosis and treatment of abdominal aortic aneurysms,
using a novel imaging protocol. Image alignment was
compared with manual registration performed by
experienced observers and mostly displayed sub-pixel
accuracy. Integration of non-rigid registration will be
convenient and this method will be applied to cardiac MR
data in the future.
This abstract and the presentation materials are available to members only;
a login is required.
Join Here
