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Improving liver fibrosis diagnosis based on forward and backward second harmonic generation signals

Author(s)
Peng, Qiwen; Zhuo, Shuangmu; Yu, Hanry; So, Peter T. C.
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.

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Abstract
The correlation of forward second harmonic generation (SHG) signal and backward SHG signal in different liver fibrosis stages was investigated. We found that three features, including the collagen percentage for forward SHG, the collagen percentage for backward SHG, and the average intensity ratio of two kinds of SHG signals, can quantitatively stage liver fibrosis in thioacetamide-induced rat model. We demonstrated that the combination of all three features by using a support vector machine classification algorithm can provide a more accurate prediction than each feature alone in fibrosis diagnosis.
Date issued
2015-02
URI
http://hdl.handle.net/1721.1/119881
Department
Massachusetts Institute of Technology. Department of Biological Engineering; Massachusetts Institute of Technology. Department of Mechanical Engineering
Journal
Applied Physics Letters
Publisher
American Institute of Physics (AIP)
Citation
Peng, Qiwen et al. “Improving Liver Fibrosis Diagnosis Based on Forward and Backward Second Harmonic Generation Signals.” Applied Physics Letters 106, 8 (February 2015): 083701 © 2015 AIP Publishing LLC
Version: Final published version
ISSN
0003-6951
1077-3118

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