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Proceedings Paper

A four class model for digital breast histopathology using high-definition Fourier transform infrared (FT-IR) spectroscopic imaging
Author(s): Shachi Mittal; Tomasz P. Wrobel; L. Suzanne Leslie; Andre Kadjacsy-Balla; Rohit Bhargava
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Paper Abstract

High-definition (HD) Fourier transform infrared (FT-IR) spectroscopic imaging is an emerging technique that not only enables chemistry-based visualization of tissue constituents, and label free extraction of biochemical information but its higher spatial detail makes it a potentially useful platform to conduct digital pathology. This methodology, along with fast and efficient data analysis, can enable both quantitative and automated pathology. Here we demonstrate a combination of HD FT-IR spectroscopic imaging of breast tissue microarrays (TMAs) with data analysis algorithms to perform histologic analysis. The samples comprise four tissue states, namely hyperplasia, dysplasia, cancerous and normal. We identify various cell types which would act as biomarkers for breast cancer detection and differentiate between them using statistical pattern recognition tools i.e. Random Forest (RF) and Bayesian algorithms. Feature optimization is integrally carried out for the RF algorithm, reducing computation time as well as redundant spectral features. We achieved an order of magnitude reduction in the number of features with comparable prediction accuracy to that of the original feature set. Together, the demonstration of histology and selection of features paves the way for future applications in more complex models and rapid data acquisition.

Paper Details

Date Published: 23 March 2016
PDF: 8 pages
Proc. SPIE 9791, Medical Imaging 2016: Digital Pathology, 979118 (23 March 2016); doi: 10.1117/12.2217358
Show Author Affiliations
Shachi Mittal, Beckman Institute for Advanced Science and Technology (United States)
Univ. of Illinois at Urbana-Champaign (United States)
Tomasz P. Wrobel, Beckman Institute for Advanced Science and Technology (United States)
L. Suzanne Leslie, Beckman Institute for Advanced Science and Technology (United States)
Univ. of Illinois at Urbana-Champaign (United States)
Andre Kadjacsy-Balla, Univ. of Illinois at Chicago (United States)
Univ. of Illinois Cancer Ctr. (United States)
Rohit Bhargava, Beckman Institute for Advanced Science and Technology (United States)
Univ. of Illinois at Urbana-Champaign (United States)
Univ. of Illinois Cancer Ctr. (United States)


Published in SPIE Proceedings Vol. 9791:
Medical Imaging 2016: Digital Pathology
Metin N. Gurcan; Anant Madabhushi, Editor(s)

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