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As a kind of carcinoma with extremely high mortality and morbidity, there are immense demand for early detection and diagnosis of gastric carcinoma. At present, in medical research, the initial detection of gastric tumors mainly uses the laser detection methods. The Monte Carlo method has good adaptability for exploring the process of photon transportation, therefore, it has the value of extension and application in the research of photons’ transportation in biological tissues. Through exploring the influence of the tumor in gastric tissue on the photon transmission, it can help determine the existence of gastric tumor. After established the corresponding model, we using the program to perform the fitting process, analysising the result then we can draw a conclusion that: according to the trajectory analysis of photons, gastric tumors absorb more photons than the gastric tissues, and such basic features can be used to determine the existence of gastric tumors. Through the analysis of optical absorption density and fluence rate: when photons initially enter the first gastric tissue layer(the Z-axis 0-0.2cm region), because the water layer’s weak optical absorption and scattering effects, optical absorption decreases slowly: from 0.0805cm-1 drop to 0.073cm-1. After entering the second layer, the layer of gastric tissue, because the absorption and scattering effect of gastric tissue is higher than water, the optical absorption density rises sharply to 8.7028cm-1, then with the photon weight decreasing, the optical absorption density continues to drop to 0.7128cm-1. After entering the third layer, the layer of gastric tumor, the optical absorption density rises again. When z=0.5cm, the optical absorption density approaches to 1.8848cm-1 and then slowly drops to 0.1338cm-1. Finally, photons enter the second layer of gastric tissue and water layers, and continue to decrease to approach 0cm-1. These data demonstrate that there are effects of gastric tumor on photon transport in gastric tissues. This research will also provide reference and theoretical guidance for the optical imaging and diagnosis of gastric tumors.
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