A four class model for digital breast histopathology using high-definition Fourier transform infrared (FT-IR) spectroscopic imaging

Shachi Mittal, Tomasz P. Wrobel, L. S. Leslie, Andre Kadjacsy-Balla, Rohit Bhargava

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2016
Subtitle of host publicationDigital Pathology
EditorsAnant Madabhushi, Metin N. Gurcan
ISBN (Electronic)9781510600263
StatePublished - 2016
Event4th Medical Imaging 2016: Digital Pathology - San Diego, United States
Duration: Mar 2 2016Mar 3 2016

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


Other4th Medical Imaging 2016: Digital Pathology
Country/TerritoryUnited States
CitySan Diego


  • FTIR
  • High-Definition
  • Random Forest
  • automated pathology
  • breast cancer
  • four class classifier

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging
  • Biomaterials


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