Imaging white blood cells using a snapshot hyperspectral imaging system

Christopher J. Robison; Christopher Kolanko; Thirimachos Bourlai; Jeremy M. Dawson

doi:10.1117/12.2177218

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21 May 2015 Imaging of blood cells based on snapshot Hyper-Spectral Imaging systems

Christopher J. Robison, Christopher Kolanko, Thirimachos Bourlai, Jeremy M. Dawson

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Proceedings Volume 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI; 94721L (2015) https://doi.org/10.1117/12.2177218
Event: SPIE Defense + Security, 2015, Baltimore, Maryland, United States

Abstract

Snapshot Hyper-Spectral imaging systems are capable of capturing several spectral bands simultaneously, offering coregistered images of a target. With appropriate optics, these systems are potentially able to image blood cells in vivo as they flow through a vessel, eliminating the need for a blood draw and sample staining. Our group has evaluated the capability of a commercial Snapshot Hyper-Spectral imaging system, the Arrow system from Rebellion Photonics, in differentiating between white and red blood cells on unstained blood smear slides. We evaluated the imaging capabilities of this hyperspectral camera; attached to a microscope at varying objective powers and illumination intensity. Hyperspectral data consisting of 25, 443x313 hyperspectral bands with ~3nm spacing were captured over the range of 419 to 494nm. Open-source hyper-spectral data cube analysis tools, used primarily in Geographic Information Systems (GIS) applications, indicate that white blood cells features are most prominent in the 428-442nm band for blood samples viewed under 20x and 50x magnification over a varying range of illumination intensities. These images could potentially be used in subsequent automated white blood cell segmentation and counting algorithms for performing in vivo white blood cell counting.

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Christopher J. Robison, Christopher Kolanko, Thirimachos Bourlai, and Jeremy M. Dawson "Imaging of blood cells based on snapshot Hyper-Spectral Imaging systems", Proc. SPIE 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI, 94721L (21 May 2015); https://doi.org/10.1117/12.2177218

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