Improved Diagnostics Using Polarization Imaging and Artificial Neural Networks

Simple item page
dc.contributor.authorXuan, Jianhuaen
dc.contributor.authorKlimach, Uween
dc.contributor.authorZhao, Hongzhien
dc.contributor.authorChen, Qiushuien
dc.contributor.authorZou, Yingyinen
dc.contributor.authorWang, Yueen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2017-09-18T10:04:18Zen
dc.date.available2017-09-18T10:04:18Zen
dc.date.issued2007-11-06en
dc.date.updated2017-09-18T10:04:18Zen
dc.description.abstractIn recent years, there has been an increasing interest in studying the propagation of polarized light in biological cells and tissues. This paper presents a novel approach to cell or tissue imaging using a full Stokes imaging system with advanced polarization image analysis algorithms for improved diagnostics. The key component of the Stokes imaging system is the electrically tunable retarder, enabling high-speed operation of the system to acquire four intensity images sequentially. From the acquired intensity images, four Stokes vector images can be computed to obtain complete polarization information. Polarization image analysis algorithms are then developed to analyze Stokes polarization images for cell or tissue classification. Specifically, wavelet transforms are first applied to the Stokes components for initial feature analysis and extraction. Artificial neural networks (ANNs) are then used to extract diagnostic features for improved classification and prediction. In this study, phantom experiments have been conducted using a prototyped Stokes polarization imaging device. In particular, several types of phantoms, consisting of polystyrene latex spheres in various diameters, were prepared to simulate different conditions of epidermal layer of skin. The experimental results from phantom studies and a plant cell study show that the classification performance using Stokes images is significantly improved over that using the intensity image only.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationJianhua Xuan, Uwe Klimach, Hongzhi Zhao, Qiushui Chen, Yingyin Zou, and Yue Wang, “Improved Diagnostics Using Polarization Imaging and Artificial Neural Networks,” International Journal of Biomedical Imaging, vol. 2007, Article ID 74143, 11 pages, 2007. doi:10.1155/2007/74143en
dc.identifier.doihttps://doi.org/10.1155/2007/74143en
dc.identifier.urihttp://hdl.handle.net/10919/79070en
dc.language.isoenen
dc.publisherHindawien
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.holderCopyright © 2007 Jianhua Xuan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleImproved Diagnostics Using Polarization Imaging and Artificial Neural Networksen
dc.title.serialInternational Journal of Biomedical Imagingen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

Files

Original bundle
Now showing 1 - 2 of 2
Name:
IJBI.2007.074143.xml
Size:
8.13 KB
Format:
Extensible Markup Language
Download
Thumbnail Image
Name:
IJBI.2007.074143.pdf
Size:
2.3 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
Name:
license.txt
Size:
1.5 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Journal Articles, Hindawi Press
Scholarly Works, Electrical and Computer Engineering