Monte Carlo Probability To Determine Attenuation Coefficient In Identifying The Selectivity Properties Of Near-Infrared-Based Materials
DOI:
https://doi.org/10.33387/protk.v11i3.7717Kata Kunci:
Attenuation Coefficient, Imaging, Monte carlo, Tranmittance, Selectivity.Abstrak
Accurate attenuation coefficient measurements are able to display the nature of selectivity in an image. The methods used to measure the attenuation coefficient are Monte Carlo probability and linear regression models. This attenuation coefficient will appear if an image is taken in transmit mode. Selectivity properties are characterized by contrast ratios between different materials. In this transmission mode, if a near-infrared beam with a different wavelength is passed, it will produce different intensity values depending on the type of wavelength. According to Beer-Lambert's law, the intensity value will experience attenuation depending on the exponential function of the attenuation coefficient and thickness. By using Monte Carlo probability, we get the thickness value of a material per point. This thickness value is then displayed in image form. This thickness function is then used to display an image. The near-infrared wavelengths used are 780 nm and 808 nm. The results show that Monte Carlo probability shows more selectivity than the linear regression method. The wavelength of 808 nm can show more selectivity properties than 780 nm.
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. Yamato, H., et al., Monte Carlo evaluation of in vivo neuroimaging using quantum dots with fluorescence in the second window of near infrared region. Advanced Biomedical Engineering, 2019. 8: p. 105-109.
. Ferraioli, G., et al., Performance of the attenuation imaging technology in the detection of liver steatosis. Journal of Ultrasound in Medicine, 2021. 40(7): p. 1325-1332.
. Aminoto, T., P.S. Priambodo, and H. Sudibyo, Image Decomposition Technique Based on Near-Infrared Transmission. Journal of Imaging, 2022. 8(12): p. 322.
. Merlo, S., et al., A VCSEL-Based NIR transillumination system for morpho-functional imaging. Sensors, 2019. 19(4): p. 851.
. Pansare, V.J., et al., Review of long-wavelength optical and NIR imaging materials: contrast agents, fluorophores, and multifunctional nano carriers. Chemistry of materials, 2012. 24(5): p. 812-827.
.Omer, H., Radiobiological effects and medical applications of non-ionizing radiation. Saudi journal of biological sciences, 2021. 28(10): p. 5585-5592.
. Tan, D.-X., et al., Melatonin: Both a messenger of darkness and a participant in the cellular actions of non-visible solar radiation of near infrared light. Biology, 2023. 12(1): p. 89.
. Marinho, M.A.G., et al., Interaction between near-infrared radiation and temozolomide in a glioblastoma multiform cell line: A treatment strategy? Cellular and Molecular Neurobiology, 2021. 41(1): p. 91-104.
. Onorato, P., et al., The Beer Lambert law measurement made easy. Physics Education, 2018. 53(3): p. 035033.
. Konishi, S., Introduction to multivariate analysis: Linear and nonlinear modeling. 2014. 1-309.
. Casasanta, G., F. Falcini, and R. Garra, Beer–Lambert law in photochemistry: A new approach. Journal of Photochemistry and Photobiology A: Chemistry, 2022. 432: p. 114086.
. Mahmoudi, M.R., On comparing two dependent linear and nonlinear regression models. Journal of Testing and Evaluation, 2018. 47(1): p. 449-458.
. Priambodo, P.S., T. Aminoto, and B. Basari, Decomposition Technique for Bio-Transmittance Imaging Based on Attenuation Coefficient Matrix Inverse. Journal of Imaging, 2024. 10(1): p. 22.
. Kirana, K.C. and M. Kom, PENGOLAHAN CITRA DIGITAL: Teori dan Penerapan Pengolahan Citra Digital pada Deteksi Wajah. 2021: Ahlimedia Book.
. Barbu, A. and S.-C. Zhu, Monte Carlo Methods. Vol. 35. 2020: Springer.
. Luengo, D., et al., A survey of Monte Carlo methods for parameter estimation. EURASIP Journal on Advances in Signal Processing, 2020. 2020: p. 1-62.
. Surendra, J., et al., Forecast and trend analysis of gold prices in India using auto regressive integrated moving average model. J. Math. Comput. Sci., 2021. 11(2): p. 1166-1175.
. AMINOTO, T., Identifikasi Sifat Selektifitas Jaringan Biologi pada Spektrum Near-Infrared dengan Citra menggunakan Hukum Beer-Lambert. ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika, 2024. 12(1): p. 23.
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