Chinese Optics Letters, Volume. 18, Issue 4, 041701(2020)
Bone mineral density value evaluation based on photoacoustic spectral analysis combined with deep learning method
Fig. 1. (a) Schematic diagram of the experimental setup. (b) The image of actual experimental installation.
Fig. 2. Step of soaking swine slices into EDTA solution to imitate the process of bone loss.
Fig. 3. Specific structure of adopted fully connected seven-layer network, and the details of layer 1 and layer 2 are presented in the right as an example.
Fig. 4. Each diagram corresponds to one stage of signal processing. (a) The raw time domain PA signal. (b) Truncated time domain PA signal. (c) Time domain PA signal of further sampling in (b); it retains the information of (b) but has a larger interval between adjacent points (scatter diagrams are utilized to discriminate them). (d) The result of (c) after Fourier transform as an example illustration of the eventual normalized input of the network.
Fig. 5. Diagram of actual BMD value and its corresponding absolute error compared with the network fitting one.
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Xue Zhou, Zhibin Jin, Ting Feng, Qian Cheng, Xueding Wang, Yao Ding, Hongchen Zhan, Jie Yuan, "Bone mineral density value evaluation based on photoacoustic spectral analysis combined with deep learning method," Chin. Opt. Lett. 18, 041701 (2020)
Category: Biomedical Optics
Received: Oct. 1, 2019
Accepted: Dec. 19, 2019
Posted: Dec. 19, 2019
Published Online: Apr. 2, 2020
The Author Email: Hongchen Zhan (hongchen_zhan@jlxy.nju.edu.cn), Jie Yuan (yuanjie@nju.edu.cn)