Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/29538
Title: 4D Non-rigid registration of renal dynamic contrast enhanced MRI data
Authors: FOO JIT SOON
Keywords: Non-rigid registration, perfusion MRI, graph-cuts, demons, renography, grow-cut segmentation
Issue Date: 29-Jul-2011
Source: FOO JIT SOON (2011-07-29). 4D Non-rigid registration of renal dynamic contrast enhanced MRI data. ScholarBank@NUS Repository.
Abstract: This thesis presents a near-automatic non-rigid registration algorithm requiring minimal user interaction for renal dynamic contrast enhanced (DCE) MR images. The 12 patients? dataset (24 kidney volumes) to be registered were acquired on a 1.5T scanner of size 256 x 256 x 40 (voxel resolution of 1.66mm x 1.66mm x 2.5mm) with the number of static volumes in each dataset varying from 31 to 41. A multi-level registration algorithm is proposed to first account for initial large translational errors, followed by compensating for local deformations of the kidney. A graph-cut optimization technique integrating local gradient information into an energy function solves the initial problem of 3D translational registration. A motion/noise free pseudo ground-truth dataset is then estimated from the whole time sequence of each kidney dataset obtained after translational registration. Finally, the demons algorithm is used to register each 3-D volume (as floating image) to its corresponding estimated volume (as reference image) at each time frame. Experimental results on patient data demonstrate that the proposed algorithm is able to: (1) perform initial translational registration accurately with an error of up to 5 voxels; (2) correctly estimate the pseudo ground-truth dataset, and (3) achieve non-rigid registration of 4D time-series of renal DCE MRI data.
URI: http://scholarbank.nus.edu.sg/handle/10635/29538
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