dc.contributor.author | Trukhan, Stanislau | |
dc.contributor.author | Tafintseva, Valeria | |
dc.contributor.author | Tøndel, Kristin | |
dc.contributor.author | Großerueschkamp, Frederik | |
dc.contributor.author | Mosig, Axel | |
dc.contributor.author | Kovalev, Vassili | |
dc.contributor.author | Gerwert, Klaus | |
dc.contributor.author | Kohler, Achim | |
dc.date.accessioned | 2021-11-17T10:46:23Z | |
dc.date.available | 2021-11-17T10:46:23Z | |
dc.date.created | 2020-10-05T09:54:06Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 1864-063X | |
dc.identifier.uri | https://hdl.handle.net/11250/2830069 | |
dc.description.abstract | 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. | |
dc.language.iso | eng | |
dc.title | Grayscale representation of infrared microscopy images by Extended Multiplicative Signal Correction for registration with histological images | |
dc.type | Peer reviewed | |
dc.type | Journal article | |
dc.description.version | publishedVersion | |
dc.source.journal | Journal of Biophotonics | |
dc.identifier.doi | 10.1002/jbio.201960223 | |
dc.identifier.cristin | 1836962 | |
dc.relation.project | Norges forskningsråd: 289518 | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |