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Journal of Biomedical Optics

Hyperspectral imaging and quantitative analysis for prostate cancer detection
Author(s): Hamed Akbari; Luma Halig; David M. Schuster; Baowei Fei; Adeboye Osunkoya; Viraj Master; Peter Nieh; Georgia Chen
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Paper Abstract

Hyperspectral imaging (HSI) is an emerging modality for various medical applications. Its spectroscopic data might be able to be used to noninvasively detect cancer. Quantitative analysis is often necessary in order to differentiate healthy from diseased tissue. We propose the use of an advanced image processing and classification method in order to analyze hyperspectral image data for prostate cancer detection. The spectral signatures were extracted and evaluated in both cancerous and normal tissue. Least squares support vector machines were developed and evaluated for classifying hyperspectral data in order to enhance the detection of cancer tissue. This method was used to detect prostate cancer in tumor-bearing mice and on pathology slides. Spatially resolved images were created to highlight the differences of the reflectance properties of cancer versus those of normal tissue. Preliminary results with 11 mice showed that the sensitivity and specificity of the hyperspectral image classification method are 92.8% to 2.0% and 96.9% to 1.3%, respectively. Therefore, this imaging method may be able to help physicians to dissect malignant regions with a safe margin and to evaluate the tumor bed after resection. This pilot study may lead to advances in the optical diagnosis of prostate cancer using HSI technology.

Paper Details

Date Published: 6 July 2012
PDF: 11 pages
J. Biomed. Opt. 17(7) 076005 doi: 10.1117/1.JBO.17.7.076005
Published in: Journal of Biomedical Optics Volume 17, Issue 7
Show Author Affiliations
Hamed Akbari, Emory Univ. (United States)
Luma Halig, Emory Univ. (United States)
David M. Schuster, Emory Univ. (United States)
Baowei Fei, Emory Univ. (United States)
Adeboye Osunkoya, Emory Univ. (United States)
Viraj Master, Emory Univ. (United States)
Peter Nieh, Emory Univ. (United States)
Georgia Chen, Emory Univ. (United States)

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