J. Montagner, V. Barra, J.-P. Reveillès, and J.-Y. Boire (France)
Medical image processing, Activity quantitation, Multimodality, Multiresolution, Data fusion, Geometrical model
The multimodality approach for the quantitative study of SPECT medical images consists in matching volumes of interest from a MR anatomical image to the functional data set. We propose a new method for the management of such multiresolution data, in which a geometrical model allows an accurate correspondence of voxels from both images, while preserving at best both original information. We use this matching method to replace the interpolation step in the compulsory image registration of the data fusion process used for activity quantitation. Compared with common multimodality approaches, the method provides coherent results with a lower estimation error of the normalized tracer binding level.
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