Abstract
Fourier transform infrared (FT-IR) spectroscopic imaging is an emerging technique that provides both spatially and chemically resolved information. The rich chemical content of data may be utilized for computer-aided determinations of structure and pathologic state (cancer diagnosis) in histological tissue sections for Prostate and Breast Cancer. Recent results show that tissue type (histological) classification can be performed to an accuracy [1] of 94% to 99% and cancer diagnosis can be performed with an accuracy of about [2] 80% on a microscopic ( 6m) length scale. One of the primary causes of reduction in classification accuracy is the systematic errors caused by distortions in the infrared spectra of tissues resulting from the nature of data acquisition. Here, we present a rigorous model for the interaction of infrared light with the tissue sample using coupled wave analysis and characterize the nature of these distortions. In particular, we demonstrate the spectral effects of changing the thickness of homogeneous samples and scattering from boundaries of two regions in spatially heterogeneous samples. Modeling these optical distortions provides a fundamental understanding of systematic errors in FT-IR measurements and is important to improving accuracy of automated cancer tissue histopathology.
| Original language | English (US) |
|---|---|
| Title of host publication | 2011 8th IEEE International Symposium on Biomedical Imaging |
| Subtitle of host publication | From Nano to Macro, ISBI'11 |
| Pages | 738-741 |
| Number of pages | 4 |
| DOIs | |
| State | Published - Nov 2 2011 |
| Event | 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States Duration: Mar 30 2011 → Apr 2 2011 |
Publication series
| Name | Proceedings - International Symposium on Biomedical Imaging |
|---|---|
| ISSN (Print) | 1945-7928 |
| ISSN (Electronic) | 1945-8452 |
Other
| Other | 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 |
|---|---|
| Country | United States |
| City | Chicago, IL |
| Period | 3/30/11 → 4/2/11 |
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Keywords
- Cancer
- FT-IR
- Infrared
- Spectroscopic Imaging
- Tissue classification
ASJC Scopus subject areas
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging
Cite this
Modeling fourier transform infrared spectroscopic imaging of Prostate and Breast Cancer tissue specimens. / Reddy, Rohith; Davis, Brynmor; Carney, Paul Scott; Bhargava, Rohit.
2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11. 2011. p. 738-741 5872511 (Proceedings - International Symposium on Biomedical Imaging).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Modeling fourier transform infrared spectroscopic imaging of Prostate and Breast Cancer tissue specimens
AU - Reddy, Rohith
AU - Davis, Brynmor
AU - Carney, Paul Scott
AU - Bhargava, Rohit
PY - 2011/11/2
Y1 - 2011/11/2
N2 - Fourier transform infrared (FT-IR) spectroscopic imaging is an emerging technique that provides both spatially and chemically resolved information. The rich chemical content of data may be utilized for computer-aided determinations of structure and pathologic state (cancer diagnosis) in histological tissue sections for Prostate and Breast Cancer. Recent results show that tissue type (histological) classification can be performed to an accuracy [1] of 94% to 99% and cancer diagnosis can be performed with an accuracy of about [2] 80% on a microscopic ( 6m) length scale. One of the primary causes of reduction in classification accuracy is the systematic errors caused by distortions in the infrared spectra of tissues resulting from the nature of data acquisition. Here, we present a rigorous model for the interaction of infrared light with the tissue sample using coupled wave analysis and characterize the nature of these distortions. In particular, we demonstrate the spectral effects of changing the thickness of homogeneous samples and scattering from boundaries of two regions in spatially heterogeneous samples. Modeling these optical distortions provides a fundamental understanding of systematic errors in FT-IR measurements and is important to improving accuracy of automated cancer tissue histopathology.
AB - Fourier transform infrared (FT-IR) spectroscopic imaging is an emerging technique that provides both spatially and chemically resolved information. The rich chemical content of data may be utilized for computer-aided determinations of structure and pathologic state (cancer diagnosis) in histological tissue sections for Prostate and Breast Cancer. Recent results show that tissue type (histological) classification can be performed to an accuracy [1] of 94% to 99% and cancer diagnosis can be performed with an accuracy of about [2] 80% on a microscopic ( 6m) length scale. One of the primary causes of reduction in classification accuracy is the systematic errors caused by distortions in the infrared spectra of tissues resulting from the nature of data acquisition. Here, we present a rigorous model for the interaction of infrared light with the tissue sample using coupled wave analysis and characterize the nature of these distortions. In particular, we demonstrate the spectral effects of changing the thickness of homogeneous samples and scattering from boundaries of two regions in spatially heterogeneous samples. Modeling these optical distortions provides a fundamental understanding of systematic errors in FT-IR measurements and is important to improving accuracy of automated cancer tissue histopathology.
KW - Cancer
KW - FT-IR
KW - Infrared
KW - Spectroscopic Imaging
KW - Tissue classification
UR - http://www.scopus.com/inward/record.url?scp=80055038378&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80055038378&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2011.5872511
DO - 10.1109/ISBI.2011.5872511
M3 - Conference contribution
AN - SCOPUS:80055038378
SN - 9781424441280
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 738
EP - 741
BT - 2011 8th IEEE International Symposium on Biomedical Imaging
ER -