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Details of Grant 

EPSRC Reference: GR/J90183/01
Principal Investigator: Hawkes, Professor D
Other Investigators:
Hill, Professor DL Colchester, Professor ACF Adam, Professor A
Gleeson, Professor M Hill, Dr D Cox, Dr T
Strong, Mr A Strong, Mr J
Researcher Co-Investigators:
Project Partners:
Department: Radiological Sciences
Organisation: United Medical & Dental Schools
Scheme: Standard Research (Pre-FEC)
Starts: 01 July 1994 Ends: 30 June 1997 Value (£): 155,268
EPSRC Research Topic Classifications:
Image & Vision Computing
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors Healthcare
Related Grants:
Panel History:  
Summary on Grant Application Form
To devise appropriate computational methodology in tracking and deformation such that 3D pre-operative representations of the patient can be updated with intra-operative spatial information from a 3D localiser, ultrasound or x-ray fluoroscopy. Progress:1. Collection of data.We have collected volumetric MR datasets of the abdomen of a volunteer whose position in the MR scanner was changed between acquisitions. We have also collected MR, CT and PET images of the head and neck of patients with squamous cell carcinoma which demonstrate patient movement between scan acquisitions. We are using a mechanical localiser to collect data on point fudicials during operations. We have collected pre-operative CT, MR and functional MR, intra-operative photographs, point landmark coordinates and post-operative MR of a patient undergoing epilepsy surgery where there was significant tissue distortion during and after the operation. We have almost completed modification of a stereo operating microscope to provide accurate overlay of rendered pre-operative 3D image data on the operative scene. This will enable us to determine tissue movement in the focal planes of the stereo microscope for procedures in the skull base and in ENT surgery. Limited depth resolution may also be possible. 2. Computational methodologyA system for 3D warping of voxel data based on point fiducials has been implemented. A range of warping functions have been incorporated including the thin plate spline and Gaussian functions of different kernel sizes. Initial tests are being carried out on example datasets to compare each functions ability to follow soft tissue movement and deformation. Initial results on volumetric MR data sets of the lower spine show that estimates of the position of the aorta relative to the spine is significantly improved. We are now testing the algorithms on data sets collected in the head and neck (for staging squamous cell carcinoma and planning surgery) and in the brain (for planning epilepsy surgery).
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