Published in:
01-11-2003 | Diagnostic Neuroradiology
Enhancing accuracy of magnetic resonance image fusion by defining a volume of interest
Authors:
B. M. Hoelper, F. Soldner, R. Lachner, R. Behr
Published in:
Neuroradiology
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Issue 11/2003
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Abstract
We compared the registration accuracy for corresponding anatomical landmarks in two MR images after fusing the complete volume (CV) and a defined volume of interest (VOI) of both MRI data sets. We carried out contrast-enhanced T1-weighted gradient-echo and T2-weighted fast spin-echo MRI (matrix 256×256) in 39 cases. The CV and a defined VOI data set were each fused using prototype software. We measured and analysed the distance between 25 anatomical landmarks in predefined areas identified at levels L1–L5 corresponding to defined axial sections. Fusion technique, landmark areas and level of fusion were further processed using a feed-forward neural network to calculate the difference which can be expected based on the measurements. We identified 975 landmarks for both T1- and T2-weighted images and found a significant difference in registration accuracy (P<0.01) for all landmarks between CV (1.6±1.2 mm) and VOI (0.7±1.0 mm). From cranial (L1) to caudal (L5), mean deviations were: L1 CV 1.5 mm, VOI 0.5 mm; L2 CV 1.8 mm, VOI 0.4 mm; L3 CV 1.7 mm, VOI 0.4 mm; L4 CV 1.6 mm, VOI 0.6 mm; and L5 CV 1.6 mm, VOI 1.6 mm. Neural network analysis predicted a higher accuracy for VOI (0.05–0.15 mm) than for CV fusion (0.9–1.6 mm). Deviations due to magnetic susceptibility changes between air and tissue seen on gradient-echo images can decrease fusion accuracy. Our VOI fusion technique improves image fusion accuracy to <0.5 mm by excluding areas with marked susceptibility changes.