Share Email Print
cover

Proceedings Paper • new

Multi-modal image fusion for multispectral super-resolution in microscopy
Author(s): Neel Dey; Shijie Li; Katharina Bermond; Rainer Heintzmann; Christine A. Curcio; Thomas Ach; Guido Gerig
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Spectral imaging is a ubiquitous tool in modern biochemistry. Despite acquiring dozens to thousands of spectral channels, existing technology cannot capture spectral images at the same spatial resolution as structural microscopy. Due to partial voluming and low light exposure, spectral images are often difficult to interpret and analyze. This highlights a need to upsample the low-resolution spectral image by using spatial information contained in the high-resolution image, thereby creating a fused representation with high specificity both spatially and spectrally. In this paper, we propose a framework for the fusion of co-registered structural and spectral microscopy images to create super-resolved representations of spectral images. As a first application, we super-resolve spectral images of ex-vivo retinal tissue imaged with confocal laser scanning microscopy, by using spatial information from structured illumination microscopy. Second, we super-resolve mass spectroscopic images of mouse brain tissue, by using spatial information from high-resolution histology images. We present a systematic validation of model assumptions crucial towards maintaining the original nature of spectra and the applicability of super-resolution. Goodness-of-fit for spectral predictions are evaluated through functional R2 values, and the spatial quality of the super-resolved images are evaluated using normalized mutual information.

Paper Details

Date Published: 15 March 2019
PDF: 7 pages
Proc. SPIE 10949, Medical Imaging 2019: Image Processing, 109490D (15 March 2019); doi: 10.1117/12.2512598
Show Author Affiliations
Neel Dey, NYU Tandon School of Engineering (United States)
Shijie Li, NYU Tandon School of Engineering (United States)
Katharina Bermond, Universitätsklinikum Würzburg (Germany)
Rainer Heintzmann, Friedrich-Schiller-Univ. Jena (Germany)
Leibniz-Institut für Photonische Technologien e.V. (Germany)
Christine A. Curcio, The Univ. of Alabama at Birmingham (United States)
Thomas Ach, Universitätsklinikum Würzburg (Germany)
Guido Gerig, NYU Tandon School of Engineering (United States)


Published in SPIE Proceedings Vol. 10949:
Medical Imaging 2019: Image Processing
Elsa D. Angelini; Bennett A. Landman, Editor(s)

© SPIE. Terms of Use
Back to Top