Red, green, and blue gray-value shift-based approach to whole-field imaging for tissue diagnostics

Identification of abnormal pathology in situ remains one of the challenges of medicine. The interpretation of tissue conditions relies mainly on optical assessment, which can be difficult due to inadequate visual differences or poor color delineation. We propose a methodology to identify regions of...

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Main Authors: Krishnan, Sathiyamoorthy, Krishnan, Mohankumar Valiyambath, Matham, Murukeshan Vadakke, Parasuraman, Padmanabhan, Joseph, James, Bhakoo, Kishore K.
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2013
Online Access:https://hdl.handle.net/10356/98245
http://hdl.handle.net/10220/10900
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-982452023-03-04T17:19:10Z Red, green, and blue gray-value shift-based approach to whole-field imaging for tissue diagnostics Krishnan, Sathiyamoorthy Krishnan, Mohankumar Valiyambath Matham, Murukeshan Vadakke Parasuraman, Padmanabhan Joseph, James Bhakoo, Kishore K. School of Mechanical and Aerospace Engineering Identification of abnormal pathology in situ remains one of the challenges of medicine. The interpretation of tissue conditions relies mainly on optical assessment, which can be difficult due to inadequate visual differences or poor color delineation. We propose a methodology to identify regions of abnormal tissue in a targeted area based on red, green, blue (RGB) shift analysis employing a simple CCD color camera and light-emitting diode illumination in a whole-field-imaging scheme. The concept involves analysis of RGB components in an image with respect to a reference set of RGB values under different illumination wavelengths. The magnitude of the gray value shift is estimated by calculating the Euclidean distance between their normalized RGB coordinates. The shift values obtained using these concepts are thereafter used to construct pseudo-colored images with high contrast, enabling easy identification of abnormal areas in the tissue. Images processed from experiments conducted with excised Wistar rat colon sample (lightly doped with Alexafluor 488) and with simulated tumor (cancer cell pellet placed on colon) showed clear localization of tumor region. This proposed approach and methodology is expected to find potential applications for the in vivo diagnosis of disease. Published version 2013-07-03T02:57:43Z 2019-12-06T19:52:35Z 2013-07-03T02:57:43Z 2019-12-06T19:52:35Z 2012 2012 Journal Article Krishnan, M. V., Matham, M. V., Krishnan, S., Parasuraman, P., Joseph, J., & Bhakoo, K. K. (2012). Red, green, and blue gray-value shift-based approach to whole-field imaging for tissue diagnostics. Journal of biomedical optics, 17(7), 076010-. 1083-3668 https://hdl.handle.net/10356/98245 http://hdl.handle.net/10220/10900 10.1117/1.JBO.17.7.076010 en Journal of biomedical optics © 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). This paper was published in Journal of Biomedical Optics and is made available as an electronic reprint (preprint) with permission of Society of Photo-Optical Instrumentation Engineers (SPIE). The paper can be found at the following official DOI: [http://dx.doi.org/10.1117/1.JBO.17.7.076010]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
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language English
description Identification of abnormal pathology in situ remains one of the challenges of medicine. The interpretation of tissue conditions relies mainly on optical assessment, which can be difficult due to inadequate visual differences or poor color delineation. We propose a methodology to identify regions of abnormal tissue in a targeted area based on red, green, blue (RGB) shift analysis employing a simple CCD color camera and light-emitting diode illumination in a whole-field-imaging scheme. The concept involves analysis of RGB components in an image with respect to a reference set of RGB values under different illumination wavelengths. The magnitude of the gray value shift is estimated by calculating the Euclidean distance between their normalized RGB coordinates. The shift values obtained using these concepts are thereafter used to construct pseudo-colored images with high contrast, enabling easy identification of abnormal areas in the tissue. Images processed from experiments conducted with excised Wistar rat colon sample (lightly doped with Alexafluor 488) and with simulated tumor (cancer cell pellet placed on colon) showed clear localization of tumor region. This proposed approach and methodology is expected to find potential applications for the in vivo diagnosis of disease.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Krishnan, Sathiyamoorthy
Krishnan, Mohankumar Valiyambath
Matham, Murukeshan Vadakke
Parasuraman, Padmanabhan
Joseph, James
Bhakoo, Kishore K.
format Article
author Krishnan, Sathiyamoorthy
Krishnan, Mohankumar Valiyambath
Matham, Murukeshan Vadakke
Parasuraman, Padmanabhan
Joseph, James
Bhakoo, Kishore K.
spellingShingle Krishnan, Sathiyamoorthy
Krishnan, Mohankumar Valiyambath
Matham, Murukeshan Vadakke
Parasuraman, Padmanabhan
Joseph, James
Bhakoo, Kishore K.
Red, green, and blue gray-value shift-based approach to whole-field imaging for tissue diagnostics
author_sort Krishnan, Sathiyamoorthy
title Red, green, and blue gray-value shift-based approach to whole-field imaging for tissue diagnostics
title_short Red, green, and blue gray-value shift-based approach to whole-field imaging for tissue diagnostics
title_full Red, green, and blue gray-value shift-based approach to whole-field imaging for tissue diagnostics
title_fullStr Red, green, and blue gray-value shift-based approach to whole-field imaging for tissue diagnostics
title_full_unstemmed Red, green, and blue gray-value shift-based approach to whole-field imaging for tissue diagnostics
title_sort red, green, and blue gray-value shift-based approach to whole-field imaging for tissue diagnostics
publishDate 2013
url https://hdl.handle.net/10356/98245
http://hdl.handle.net/10220/10900
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