Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification
Author(s)Stanciu, Stefan G.; Xu, Shuoyu; Peng, Qiwen; Yan, Jie; Stanciu, George A.; Welsch, Roy E.; So, Peter T. C.; Csucs, Gabor; Yu, Hanry; ... Show more Show less
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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.
DepartmentMassachusetts Institute of Technology. Department of Biological Engineering; Massachusetts Institute of Technology. Department of Mechanical Engineering; Sloan School of Management
Nature Publishing Group
Stanciu, Stefan G., Shuoyu Xu, Qiwen Peng, Jie Yan, George A. Stanciu, Roy E. Welsch, Peter T. C. So, Gabor Csucs, and Hanry Yu. “Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification.” Sci. Rep. 4 (April 10, 2014).
Final published version