Journal
SCIENTIFIC REPORTS
Volume 4, Issue -, Pages -Publisher
NATURE RESEARCH
DOI: 10.1038/srep04636
Keywords
-
Categories
Funding
- Romanian Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI)
- SCIEX NMS-CH research fellowship [12.135]
- Swiss Universities (CRUS)
- Institute of Bioengineering and Nanotechnology, Biomedical Research Council, A*STAR
- Janssen [R-185-000-182-592]
- Singapore-MIT Alliance Computational and Systems Biology Flagship Project [C-382-641-001-091]
- SMART BioSyM and Mechanobiology Institute of Singapore [R-714-001-003-271]
- [PN-II-PT-PCCA-2011-3.2-1162]
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available