Data processing for tissue histopathology using fourier transform infrared spectral data

Frances N. Keith, Rong Kong, Anusha Pryia, Rohit Bhargava

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

Abstract

Optical microscopic examination of stained tissue by pathologists is the gold standard for the diagnosis of most cancers. Due to the human element involved, however, the process is slow, decisions are often complicated by subjective opinions and the uncertainty in diagnoses can affect therapy. Infrared spectroscopic imaging or hyperspectral molecular imaging, as opposed to optical wideband imaging, has been proposed as a viable alternative to provide automated, accurate, reproducible and useful diagnoses. Data processing to enable these applications, however, is not straightforward. Here we discuss recent advances in automatically profiling tissue and present the complexity and numerical strategies to address issues involved. Using breast cancer as an example, we show the importance of integrating statistical and mathematical tools into the analysis framework.

Original languageEnglish (US)
Title of host publicationConference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06
Pages71-75
Number of pages5
DOIs
StatePublished - Dec 1 2006
Event40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 - Pacific Grove, CA, United States
Duration: Oct 29 2006Nov 1 2006

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06
CountryUnited States
CityPacific Grove, CA
Period10/29/0611/1/06

Fingerprint

Fourier transforms
Tissue
Infrared radiation
Molecular imaging
Imaging techniques
Microscopic examination
Hyperspectral imaging
Uncertainty

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Cite this

Keith, F. N., Kong, R., Pryia, A., & Bhargava, R. (2006). Data processing for tissue histopathology using fourier transform infrared spectral data. In Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06 (pp. 71-75). [4176515] (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2006.356586

Data processing for tissue histopathology using fourier transform infrared spectral data. / Keith, Frances N.; Kong, Rong; Pryia, Anusha; Bhargava, Rohit.

Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06. 2006. p. 71-75 4176515 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

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

Keith, FN, Kong, R, Pryia, A & Bhargava, R 2006, Data processing for tissue histopathology using fourier transform infrared spectral data. in Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06., 4176515, Conference Record - Asilomar Conference on Signals, Systems and Computers, pp. 71-75, 40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06, Pacific Grove, CA, United States, 10/29/06. https://doi.org/10.1109/ACSSC.2006.356586
Keith FN, Kong R, Pryia A, Bhargava R. Data processing for tissue histopathology using fourier transform infrared spectral data. In Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06. 2006. p. 71-75. 4176515. (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2006.356586
Keith, Frances N. ; Kong, Rong ; Pryia, Anusha ; Bhargava, Rohit. / Data processing for tissue histopathology using fourier transform infrared spectral data. Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06. 2006. pp. 71-75 (Conference Record - Asilomar Conference on Signals, Systems and Computers).
@inproceedings{11e67edf208d461d879a4e03faf086ee,
title = "Data processing for tissue histopathology using fourier transform infrared spectral data",
abstract = "Optical microscopic examination of stained tissue by pathologists is the gold standard for the diagnosis of most cancers. Due to the human element involved, however, the process is slow, decisions are often complicated by subjective opinions and the uncertainty in diagnoses can affect therapy. Infrared spectroscopic imaging or hyperspectral molecular imaging, as opposed to optical wideband imaging, has been proposed as a viable alternative to provide automated, accurate, reproducible and useful diagnoses. Data processing to enable these applications, however, is not straightforward. Here we discuss recent advances in automatically profiling tissue and present the complexity and numerical strategies to address issues involved. Using breast cancer as an example, we show the importance of integrating statistical and mathematical tools into the analysis framework.",
author = "Keith, {Frances N.} and Rong Kong and Anusha Pryia and Rohit Bhargava",
year = "2006",
month = "12",
day = "1",
doi = "10.1109/ACSSC.2006.356586",
language = "English (US)",
isbn = "1424407850",
series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",
pages = "71--75",
booktitle = "Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06",

}

TY - GEN

T1 - Data processing for tissue histopathology using fourier transform infrared spectral data

AU - Keith, Frances N.

AU - Kong, Rong

AU - Pryia, Anusha

AU - Bhargava, Rohit

PY - 2006/12/1

Y1 - 2006/12/1

N2 - Optical microscopic examination of stained tissue by pathologists is the gold standard for the diagnosis of most cancers. Due to the human element involved, however, the process is slow, decisions are often complicated by subjective opinions and the uncertainty in diagnoses can affect therapy. Infrared spectroscopic imaging or hyperspectral molecular imaging, as opposed to optical wideband imaging, has been proposed as a viable alternative to provide automated, accurate, reproducible and useful diagnoses. Data processing to enable these applications, however, is not straightforward. Here we discuss recent advances in automatically profiling tissue and present the complexity and numerical strategies to address issues involved. Using breast cancer as an example, we show the importance of integrating statistical and mathematical tools into the analysis framework.

AB - Optical microscopic examination of stained tissue by pathologists is the gold standard for the diagnosis of most cancers. Due to the human element involved, however, the process is slow, decisions are often complicated by subjective opinions and the uncertainty in diagnoses can affect therapy. Infrared spectroscopic imaging or hyperspectral molecular imaging, as opposed to optical wideband imaging, has been proposed as a viable alternative to provide automated, accurate, reproducible and useful diagnoses. Data processing to enable these applications, however, is not straightforward. Here we discuss recent advances in automatically profiling tissue and present the complexity and numerical strategies to address issues involved. Using breast cancer as an example, we show the importance of integrating statistical and mathematical tools into the analysis framework.

UR - http://www.scopus.com/inward/record.url?scp=42149183473&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=42149183473&partnerID=8YFLogxK

U2 - 10.1109/ACSSC.2006.356586

DO - 10.1109/ACSSC.2006.356586

M3 - Conference contribution

AN - SCOPUS:42149183473

SN - 1424407850

SN - 9781424407859

T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers

SP - 71

EP - 75

BT - Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06

ER -