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dc.contributor.author Mostaço-Guidolin, Leila B.
dc.contributor.author Ko, Alex C.-T.
dc.contributor.author Wang, Fei
dc.contributor.author Xiang, Bo
dc.contributor.author Hewko, Mark
dc.contributor.author Tian, Ganghong
dc.contributor.author Major, Arkady
dc.contributor.author Shiomi, Masashi
dc.contributor.author Sowa, Michael G.
dc.date.accessioned 2014-06-25T16:09:16Z
dc.date.available 2014-06-25T16:09:16Z
dc.date.issued 2013-07-12
dc.identifier.citation Mostaço-Guidolin, L.B. et al. Collagen morphology and texture analysis: from statistics to classification. Scientific Reports, 3: 2190. en_US
dc.identifier.uri http://hdl.handle.net/1993/23649
dc.description.abstract In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. en_US
dc.description.sponsorship L.B. M-G acknowledges financial support from Edward R. Toporeck Graduate Fellowship, Berdie, Irvin Cohen Fellowship, Elizabeth Anne Hogan Memorial Scholarship and University of Manitoba Graduate Fellowship. This work is partially supported by National Research Council Canada, Genomics and Health initiative, and Natural Science and Engineering Research Council (NSERC) Discovery Grant in a form of student financial support. Partial support by an emerging team grant for regenerative medicine and nanomedicine from Canadian Institutes of Health Research (CIHR) is also acknowledged. en_US
dc.language.iso en en_US
dc.publisher Nature en_US
dc.subject Computational biophysics en_US
dc.subject Biophotonics en_US
dc.subject Imaging techniques en_US
dc.subject Atherosclerosis en_US
dc.title Collagen morphology and texture analysis: from statistics to classification en_US
dc.type Article en_US
dc.identifier.doi http://dx.doi.org/10.1038/srep02190


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