University of Illinois at Chicago
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Real-time interactive data mining for chemical imaging information: application to automated histopathology

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journal contribution
posted on 2014-02-19, 00:00 authored by David Mayerich, Michael Walsh, Matthew Schulmerich, Rohit Bhargava
Background: Vibrational spectroscopic imaging is now used in several fields to acquire molecular information from microscopically heterogeneous systems. Recent advances have led to promising applications in tissue analysis for cancer research, where chemical information can be used to identify cell types and disease. However, recorded spectra are affected by the morphology of the tissue sample, making identification of chemical structures difficult. Results: Extracting features that can be used to classify tissue is a cumbersome manual process which limits this technology from wide applicability. In this paper, we describe a method for interactive data mining of spectral features using GPU-based manipulation of the spectral distribution. Conclusions: This allows researchers to quickly identify chemical features corresponding to cell type. These features are then applied to tissue samples in order to visualize the chemical composition of the tissue without the use of chemical stains.


This work was funded in part by the Beckman Institute for Advanced Science and Technology, the National Institutes of Health (NIH) via grant number 1R01CA138882, the National Science Foundation (NSF) Division of Chemistry (CHE) via 0957849, and the Congressionally Directed Medical Research Program Postdoctoral Fellowship via BC101112.


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© 2013 Mayerich et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 by BioMed Central, BMC Bioinformatics


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