Share Email Print
cover

Proceedings Paper

A comparative performance study characterizing breast tissue microarrays using standard RGB and multispectral imaging
Author(s): Xin Qi; William Cukierski; David J. Foran
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

The lack of clear consensus over the utility of multispectral imaging (MSI) for bright-field imaging prompted our team to investigate the benefit of using MSI on breast tissue microarrays (TMA). We have conducted performance studies to compare MSI with standard bright-field imaging in hematoxylin stained breast tissue. The methodology has three components. The first extracts a region of interest using adaptive thresholding and morphological processing. The second performs texture feature extraction from a local binary pattern within each spectral channel and compared to features of co-occurrence matrix and texture feature coding in third component. The third component performs feature selection and classification. For each spectrum, exhaustive feature selection was used to search for the combination of features that yields the best classification accuracy. AdaBoost with a linear perceptron least-square classifier was applied. The spectra carrying the greatest discriminatory power were automatically chosen and a majority vote was used to make the final classification. 92 breast TMA discs were included in the study. Sensitivity of 0.96 and specificity of 0.89 were achieved on the multispectral data, compared with sensitivity of 0.83 and specificity of 0.85 on RGB data. MSI consistently achieved better classification results than those obtained using standard RGB images. While the benefits of MSI for unmixing multi-stained specimens are well documented, this study demonstrated statistically significant improvements in the automated analysis of single stained bright-field images.

Paper Details

Date Published: 24 February 2010
PDF: 8 pages
Proc. SPIE 7557, Multimodal Biomedical Imaging V, 75570Z (24 February 2010); doi: 10.1117/12.842067
Show Author Affiliations
Xin Qi, Univ. of Medicine and Dentistry of New Jersey (United States)
William Cukierski, Univ. of Medicine and Dentistry of New Jersey (United States)
David J. Foran, Univ. of Medicine and Dentistry of New Jersey (United States)


Published in SPIE Proceedings Vol. 7557:
Multimodal Biomedical Imaging V
Fred S. Azar; Xavier Intes, Editor(s)

© SPIE. Terms of Use
Back to Top