Abstract

Image data fusion has been developed over the last decade as an important additional visual diagnostic tool to integrate the growing amount of imaging data obtained from different medical imaging modalities. The overwhelming amount of digital information calls for data consolidation to improve clinical treatment strategies based upon anatomical and physiological imaging. Three different low level image data fusion techniques are described and their characteristics are illustrated with some rare yet key examples. We used MR images to show neurodegeneration in the cerebral peduncle of the midbrain and found that image data fusion using colors can be a valuable tool to visually assess and quantify the loss of neural cells in the Substantia Nigra pars compacta in Parkinson's disease. © 2006 Elsevier Ltd. All rights reserved.