TY - GEN
T1 - Non-invasive tumor detection using NIR light
AU - Lin, Yung Chi
AU - Tseng, Sheng Hao
AU - Chung, Pau Choo
AU - Yang, Ching Fang
AU - Wu, Ming Han
AU - Nioka, Shoko
AU - Wong, Yong Kie
PY - 2013/12/1
Y1 - 2013/12/1
N2 - This paper presents a non-invasive device with near-infrared (NIR) light for the analysis of tissue components, particularly the blood oxygen saturation and hemoglobin concentration, by using photon diffusion equation. The device equips with a multispectral (7 wavelengths) LED and multiple sensors of different spatial distances to the LED source. An optimal fitting of the measurement data obtained from these sensors is employed to achieve a more accurate estimation of the concentrations of tissue components, such as hemoglobin, water, and lipid of tissue samples, which are often referred in clinic diagnosis. Besides, Monte Carlo simulation is applied to analyze how photons transmit in tissue under different depth levels. According to the simulation results, the proposal introduces a method for tumor detection to reduce the effect of shallow layer and to increase detection accuracy for deep layer tumors. The device was also evaluated by phantoms and clinical data acquired from the patients with neck tumors. Results indicate that our device is not only sensitive to the presence of neck tumors but also can be applied to study other clinical diseases.
AB - This paper presents a non-invasive device with near-infrared (NIR) light for the analysis of tissue components, particularly the blood oxygen saturation and hemoglobin concentration, by using photon diffusion equation. The device equips with a multispectral (7 wavelengths) LED and multiple sensors of different spatial distances to the LED source. An optimal fitting of the measurement data obtained from these sensors is employed to achieve a more accurate estimation of the concentrations of tissue components, such as hemoglobin, water, and lipid of tissue samples, which are often referred in clinic diagnosis. Besides, Monte Carlo simulation is applied to analyze how photons transmit in tissue under different depth levels. According to the simulation results, the proposal introduces a method for tumor detection to reduce the effect of shallow layer and to increase detection accuracy for deep layer tumors. The device was also evaluated by phantoms and clinical data acquired from the patients with neck tumors. Results indicate that our device is not only sensitive to the presence of neck tumors but also can be applied to study other clinical diseases.
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U2 - 10.1109/BioCAS.2013.6679654
DO - 10.1109/BioCAS.2013.6679654
M3 - Conference contribution
AN - SCOPUS:84893627784
SN - 9781479914715
T3 - 2013 IEEE Biomedical Circuits and Systems Conference, BioCAS 2013
SP - 122
EP - 125
BT - 2013 IEEE Biomedical Circuits and Systems Conference, BioCAS 2013
T2 - 2013 IEEE Biomedical Circuits and Systems Conference, BioCAS 2013
Y2 - 31 October 2013 through 2 November 2013
ER -