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Experimenting liver fibrosis diagnostic by two photon excitation microscopy and Bag-of-Features image classification.

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.

journal_name

Sci Rep

journal_title

Scientific reports

authors

Stanciu SG,Xu S,Peng Q,Yan J,Stanciu GA,Welsch RE,So PT,Csucs G,Yu H

doi

10.1038/srep04636

subject

Has Abstract

pub_date

2014-04-10 00:00:00

pages

4636

issn

2045-2322

pii

srep04636

journal_volume

4

pub_type

杂志文章

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