Combined spectroscopic imaging and chemometric approach for automatically partitioning tissue types in human prostate tissue biopsies

Abigail S. Haka; Linda H. Kidder; E. Neil Lewis

doi:10.1117/12.432479

2 July 2001 Combined spectroscopic imaging and chemometric approach for automatically partitioning tissue types in human prostate tissue biopsies

Abigail S. Haka, Linda H. Kidder, E. Neil Lewis

Author Affiliations +

Proceedings Volume 4259, Biomarkers and Biological Spectral Imaging; (2001) https://doi.org/10.1117/12.432479
Event: BiOS 2001 The International Symposium on Biomedical Optics, 2001, San Jose, CA, United States

Abstract

We have applied Fourier transform infrared (FTIR) spectroscopic imaging, coupling a mercury cadmium telluride (MCT) focal plane array detector (FPA) and a Michelson step scan interferometer, to the investigation of various states of malignant human prostate tissue. The MCT FPA used consists of 64x64 pixels, each 61 micrometers ², and has a spectral range of 2-10.5 microns. Each imaging data set was collected at 16^-1 resolution, resulting in 512 image planes and a total of 4096 interferograms. In this article we describe a method for separating different tissue types contained within FTIR spectroscopic imaging data sets of human prostate tissue biopsies. We present images, generated by the Fuzzy C-Means clustering algorithm, which demonstrate the successful partitioning of distinct tissue type domains. Additionally, analysis of differences in the centroid spectra corresponding to different tissue types provides an insight into their biochemical composition. Lastly, we demonstrate the ability to partition tissue type regions in a different data set using centroid spectra calculated from the original data set. This has implications for the use of the Fuzzy C-Means algorithm as an automated technique for the separation and examination of tissue domains in biopsy samples.

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Abigail S. Haka, Linda H. Kidder, and E. Neil Lewis "Combined spectroscopic imaging and chemometric approach for automatically partitioning tissue types in human prostate tissue biopsies", Proc. SPIE 4259, Biomarkers and Biological Spectral Imaging, (2 July 2001); https://doi.org/10.1117/12.432479

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