Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification
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...
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| Formato: | Artigo |
| Idioma: | en_US |
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Nature Publishing Group
2014
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| Acceso en liña: | http://hdl.handle.net/1721.1/88228 https://orcid.org/0000-0002-0339-3685 https://orcid.org/0000-0002-9038-1622 https://orcid.org/0000-0003-4698-6488 |
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| author | Stanciu, Stefan G. Xu, Shuoyu Peng, Qiwen Yan, Jie Stanciu, George A. Welsch, Roy E. So, Peter T. C. Csucs, Gabor Yu, Hanry |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Stanciu, Stefan G. Xu, Shuoyu Peng, Qiwen Yan, Jie Stanciu, George A. Welsch, Roy E. So, Peter T. C. Csucs, Gabor Yu, Hanry |
| author_sort | Stanciu, Stefan G. |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T15:55:37Z |
| format | Article |
| id | mit-1721.1/88228 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:55:37Z |
| publishDate | 2014 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/882282022-10-02T05:06:32Z Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification Stanciu, Stefan G. Xu, Shuoyu Peng, Qiwen Yan, Jie Stanciu, George A. Welsch, Roy E. So, Peter T. C. Csucs, Gabor Yu, Hanry Massachusetts Institute of Technology. Department of Biological Engineering Massachusetts Institute of Technology. Department of Mechanical Engineering Sloan School of Management Yu, Hanry So, Peter T. C. Welsch, Roy E. 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. Romania. Executive Agency for Higher Education, Research, Development and Innovation Funding (research grant PN-II-PT-PCCA-2011-3.2-1162) Rectors' Conference of the Swiss Universities (SCIEX NMS-CH research fellowship nr. 12.135) Singapore. Agency for Science, Technology and Research (R-185-000-182-592) Singapore. Biomedical Research Council Institute of Bioengineering and Nanotechnology (Singapore) Singapore-MIT Alliance (Computational and Systems Biology Flagship Project funding (C-382-641-001-091)) Singapore-MIT Alliance for Research and Technology (SMART BioSyM and Mechanobiology Institute of Singapore (R-714-001-003-271)) 2014-07-09T14:45:14Z 2014-07-09T14:45:14Z 2014-04 2013-04 Article http://purl.org/eprint/type/JournalArticle 2045-2322 http://hdl.handle.net/1721.1/88228 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). https://orcid.org/0000-0002-0339-3685 https://orcid.org/0000-0002-9038-1622 https://orcid.org/0000-0003-4698-6488 en_US http://dx.doi.org/10.1038/srep04636 Scientific Reports Creative Commons Attribution-NonCommercial-NoDerivs 3.0 http://creativecommons.org/licenses/by-nc-nd/3.0/ application/pdf Nature Publishing Group Nature Publishing Group |
| spellingShingle | Stanciu, Stefan G. Xu, Shuoyu Peng, Qiwen Yan, Jie Stanciu, George A. Welsch, Roy E. So, Peter T. C. Csucs, Gabor Yu, Hanry Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification |
| title | Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification |
| title_full | Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification |
| title_fullStr | Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification |
| title_full_unstemmed | Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification |
| title_short | Experimenting Liver Fibrosis Diagnostic by Two Photon Excitation Microscopy and Bag-of-Features Image Classification |
| title_sort | experimenting liver fibrosis diagnostic by two photon excitation microscopy and bag of features image classification |
| url | http://hdl.handle.net/1721.1/88228 https://orcid.org/0000-0002-0339-3685 https://orcid.org/0000-0002-9038-1622 https://orcid.org/0000-0003-4698-6488 |
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