Image reconstruction of FT-IR microspectrometric data

FT-IR microspectrometry, particularly in combination with digital imaging techniques shows great promise for in-vivo and ex-vivo medical diagnosis. The statement is based on the knowledge that this method delivers information of the chemical structure and composition of a sample and the fact that any disease is linked to changes in the molecular and structural composition of cells and tissues. Typically, these changes are highly specific for a given tissue structure and are therefore potentially detectable by FT-LR microspectrometry. In this paper we present several approaches for the representation of mid-infrared microspectroscopic data acquired with high spatial resolution by the use of a MCT focal plane array (FPA) detector. The applicability of image reassembling methodologies like functional group analysis, image reconstruction based on factor analysis and artificial neural network analysis to the IR data is discussed.