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Title: Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification
Authors: Stanciu, Stefan G.
Xu, Shuoyu
Peng, Qiwen
Yan, Jie
Stanciu, George A.
Welsch, Roy E.
So, Peter T. C.
Csucs, Gabor
Yu, Hanry
Keywords: Biomedical engineering
Computer science
Issue Date: 2014
Source: Stanciu, S. G., Xu, S., Peng, Q., Yan, J., Stanciu, G. A., Welsch, R. E., et al. (2014). Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification. Scientific Reports, 4, 4636-.
Series/Report no.: Scientific Reports
Abstract: The accurate staging of liver fibrosis is of paramount importance to determine the state of disease progression, therapy responses, and to optimize disease treatment strategies. Non-linear optical microscopy techniques such as two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG) can image the endogenous signals of tissue structures and can be used for fibrosis assessment on non-stained tissue samples. While image analysis of collagen in SHG images was consistently addressed until now, cellular and tissue information included in TPEF images, such as inflammatory and hepatic cell damage, equally important as collagen deposition imaged by SHG, remain poorly exploited to date. We address this situation by experimenting liver fibrosis quantification and scoring using a combined approach based on TPEF liver surface imaging on a Thioacetamide-induced rat model and a gradient based Bag-of-Features (BoF) image classification strategy. We report the assessed performance results and discuss the influence of specific BoF parameters to the performance of the fibrosis scoring framework.
ISSN: 2045-2322
DOI: 10.1038/srep04636
Schools: School of Computer Engineering 
Research Centres: Bioinformatics Research Centre 
Rights: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license. The images in this article are included in the article's Creative Commons license, unless indicated otherwise in the image credit; if the image is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the image. To view a copy of this license, visit
Fulltext Permission: open
Fulltext Availability: With Fulltext
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