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Biomedical Photonics|2 Article(s)
Light absorption distribution of uterine tissue filled with strong scattering medium irradiated by diffused light source
Yong-ping LIN, Lan-tian LIU, Zhi-fang LI, Jian-yong CAI, and Hui LI
Determining the light absorption distribution (LAD) of uterine tissue helps the detection of endometrial carcinoma. In this work, a 3-dimensional optical model of the human uterus is proposed and examined. The model is filled with strong scattering medium (undiluted raw and homogenized milk, URHM) or air at 630 nm and 800 nm wavelengths. Monte Carlo simulations are used to find the absorption profiles of photons by transcervical laser illumination, with a cylindrically diffused light source (CDLS) or spherically diffused light source (SDLS). The results show that 800 nm is a good laser wavelength value for the detection of endometrial carcinoma by photoacoustic imaging (PAI). At the same time, the shape of the light source becomes less important in a relatively large cavity. The impacts of different scattering coefficients of CDLS on the irradiated area are demonstrated. Strong scattering medium is helpful to the il-lumination of the uterus cavity. Determining the light absorption distribution (LAD) of uterine tissue helps the detection of endometrial carcinoma. In this work, a 3-dimensional optical model of the human uterus is proposed and examined. The model is filled with strong scattering medium (undiluted raw and homogenized milk, URHM) or air at 630 nm and 800 nm wavelengths. Monte Carlo simulations are used to find the absorption profiles of photons by transcervical laser illumination, with a cylindrically diffused light source (CDLS) or spherically diffused light source (SDLS). The results show that 800 nm is a good laser wavelength value for the detection of endometrial carcinoma by photoacoustic imaging (PAI). At the same time, the shape of the light source becomes less important in a relatively large cavity. The impacts of different scattering coefficients of CDLS on the irradiated area are demonstrated. Strong scattering medium is helpful to the il-lumination of the uterus cavity.
Optoelectronics Letters
- Publication Date: Jan. 01, 2018
- Vol. 14, Issue 5, 396 (2018)
Study on the echinococcosis blood serum detection based on Raman spectroscopy combined with neural network
Jin-ying CHENG, Liang XU, Guo-dong Lü, Jun TANG, Jia-qing MO, Xiao-yi Lü, and Zhi-xian GAO
A Raman spectroscopy method combined with neural network is used for the invasive and rapid detection of echinococcosis. The Raman spectroscopy measurements are performed on two groups of blood serum samples, which are from 28 echinococcosis patients and 38 healthy persons, respectively. The normalized Raman reflection spectra show that the reflectivity of the echinococcosis blood serum is higher than that of the normal human blood serum in the wavelength ranges of 101—175 nm and 1 801—2 701 nm. Then the principal component analysis (PCA) and back propagation neural network (BPNN) model are used to obtain the diagnosis results. The diagnosis rates for healthy persons and echinococcosis persons are 93.333 3% and 90.909 1%, respectively, so the average final diagnosis rate is 92.121 2%. The results demonstrate that the Raman spectroscopy analysis of blood serum combined with PCA-BPNN has considerable potential for the non-invasive and rapid detection of echinococcosis. A Raman spectroscopy method combined with neural network is used for the invasive and rapid detection of echinococcosis. The Raman spectroscopy measurements are performed on two groups of blood serum samples, which are from 28 echinococcosis patients and 38 healthy persons, respectively. The normalized Raman reflection spectra show that the reflectivity of the echinococcosis blood serum is higher than that of the normal human blood serum in the wavelength ranges of 101—175 nm and 1 801—2 701 nm. Then the principal component analysis (PCA) and back propagation neural network (BPNN) model are used to obtain the diagnosis results. The diagnosis rates for healthy persons and echinococcosis persons are 93.333 3% and 90.909 1%, respectively, so the average final diagnosis rate is 92.121 2%. The results demonstrate that the Raman spectroscopy analysis of blood serum combined with PCA-BPNN has considerable potential for the non-invasive and rapid detection of echinococcosis.
Optoelectronics Letters
- Publication Date: Jan. 01, 2017
- Vol. 13, Issue 1, 77 (2017)
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