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. 2015 Apr 6;6(5):1589-98.
doi: 10.1364/BOE.6.001589. eCollection 2015 May 1.

Blind source separation of ex-vivo aorta tissue multispectral images

July Galeano  1 , Sandra Perez  2 , Yonatan Montoya  1 , Deivid Botina  1 , Johnson Garzón  3
Affiliations

Blind source separation of ex-vivo aorta tissue multispectral images

July Galeano et al. Biomed Opt Express. .

Abstract

Blind Source Separation methods (BSS) aim for the decomposition of a given signal in its main components or source signals. Those techniques have been widely used in the literature for the analysis of biomedical images, in order to extract the main components of an organ or tissue under study. The analysis of skin images for the extraction of melanin and hemoglobin is an example of the use of BSS. This paper presents a proof of concept of the use of source separation of ex-vivo aorta tissue multispectral Images. The images are acquired with an interference filter-based imaging system. The images are processed by means of two algorithms: Independent Components analysis and Non-negative Matrix Factorization. In both cases, it is possible to obtain maps that quantify the concentration of the main chromophores present in aortic tissue. Also, the algorithms allow for spectral absorbance of the main tissue components. Those spectral signatures were compared against the theoretical ones by using correlation coefficients. Those coefficients report values close to 0.9, which is a good estimator of the method's performance. Also, correlation coefficients lead to the identification of the concentration maps according to the evaluated chromophore. The results suggest that Multi/hyper-spectral systems together with image processing techniques is a potential tool for the analysis of cardiovascular tissue.

Keywords: (000.1430) Biology and medicine; (000.2170) Equipment and techniques; (110.4234) Multispectral and hyperspectral imaging; (170.3880) Medical and biological imaging; (170.4580) Optical diagnostics for medicine; (170.6935) Tissue characterization.

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Figures

Fig. 1
Fig. 1
Configuration of a system based on interference filters: a). white light source, b). bandpass interference filters, c).liquid guide-light, d). 10X microscope objective, e).CCD camera, and f). sample.
Fig. 2
Fig. 2
Theoretical absorbance spectra of the major chromophores present in cardiovascular tissue [9, 14].
Fig. 3
Fig. 3
(a) Image at 600nm from bovine aorta tissue obtained by interference filter-based system. The tissue was illuminated from the lumen side. (b) Sampled spectrum of the ROI denoted by arrows A and B in Fig. (a).
Fig. 4
Fig. 4
Normalized concentration maps obtained by applying NMF method on cardiovascular tissue multispectral images acquired by the interference filter-based system.
Fig. 5
Fig. 5
Normalized concentration maps obtained by applying ICA method on cardiovascular tissue multispectral images acquired by the interference filter-based system.
Fig. 6
Fig. 6
Elastic fibers of aorta media layer: a. Theoretical aorta cross-section [24], b.ICA result.
See this image and copyright information in PMC

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