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Proceedings Paper

Spectral topography of histopathological samples
Author(s): Jeremy M. Lerner; Thomas Taiwei Lu; Sandor G. Vari M.D.
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Paper Abstract

The goal of imaging spectroscopy is to obtain independent spectra from individual objects in a field-of-view. In the case of biological materials, such as histopathology samples, it has been well established that spectral characteristic can be indicative of specific diseases including cancer. Diagnosis can be enhanced by the use of probes and stains to indicate the presence of individual genome or other biologically active cell components or substances. To assess a specimen through a microscope is directly analogous to serving the Earth from space to assess natural features. This paper describes a simple and inexpensive imaging spectrometer, with an origin in remote sensing, that demonstrates that it is possible to rapidly identify evidence of disease in histopathology samples using spatially resolved spectral data. The PARISS imaging spectrometer enables a researcher to acquire multi-spectral images that yield functional maps, showing what and where biological molecules are located within a structure. It is the powerful combination of imaging and spectroscopy that provides the tools not readily available to the Life Sciences. The PARISS system incorporates a powerful hybrid neural network analysis to break the data logjam that is often associated with the acquisition and processing of multiple spectra.

Paper Details

Date Published: 9 June 1998
PDF: 8 pages
Proc. SPIE 3261, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing V, (9 June 1998); doi: 10.1117/12.310557
Show Author Affiliations
Jeremy M. Lerner, LightForm, Inc. (United States)
Thomas Taiwei Lu, Photonics Research (United States)
Sandor G. Vari M.D., Cedars-Sinai Medical Ctr. (United States)

Published in SPIE Proceedings Vol. 3261:
Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing V
Thomas Taiwei Lu; Carol J. Cogswell; Jeremy M. Lerner; Jose-Angel Conchello; Jeremy M. Lerner; Thomas Taiwei Lu; Tony Wilson, Editor(s)

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