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Fibro-C-Index: comprehensive, morphology-based quantification of liver fibrosis using second harmonic generation and
Dean C S Tai1, Nancy Tan, Shuoyu Xu
1Institute of Bioengineering and Nanotechnology, The Nanos #04-01, 31 Biopolis Way, Singapore, 138669. dtai@ibn.a-star.edu.sg
Abstract:
We develop a standardized, fully automated, quantification system for liver fibrosis assessment using second harmonic generation microscopy and a morphology-based quantification algorithm. Liver fibrosis is associated with an abnormal increase in collagen as a result of chronic liver diseases. Histopathological scoring is the most commonly used method for liver fibrosis assessment, where a liver biopsy is stained and scored by experienced pathologists. Due to the intrinsic limited sensitivity and operator-dependent variations, there exist high inter- and intraobserver discrepancies. We validate our quantification system, Fibro-C-Index, with a comprehensive animal study and demonstrate its potential application in clinical diagnosis to reduce inter- and intraobserver discrepancies.
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