Grayscale representation of infrared microscopy images by Extended Multiplicative Signal Correction for registration with histological images
Trukhan, Stanislau; Tafintseva, Valeria; Tøndel, Kristin; Großerueschkamp, Frederik; Mosig, Axel; Kovalev, Vassili; Gerwert, Klaus; Kohler, Achim
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Date
2020Metadata
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10.1002/jbio.201960223Abstract
Fourier-transform infrared (FTIR) microspectroscopy is rounding the corner to become a label-free routine method for cancer diagnosis. In order to build infrared-spectral based classifiers, infrared images need to be registered with Hematoxylin and Eosin (H&E) stained histological images. While FTIR images have a deep spectral domain with thousands of channels carrying chemical and scatter information, the H&E images have only three color channels for each pixel and carry mainly morphological information. Therefore, image representations of infrared images are needed that match the morphological information in H&E images. In this paper, we propose a novel approach for representation of FTIR images based on extended multiplicative signal correction highlighting morphological features that showed to correlate well with morphological information in H&E images. Based on the obtained representations, we developed a strategy for global-to-local image registration for FTIR images and H&E stained histological images of parallel tissue sections.