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Evaluation of Developed Thermal Distribution Prediction Algorithm Using Mass Density Distribution with CT Image

机译:用CT图像的质量密度分布评估发达的热分布预测算法

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Prior to the hyperthermia, the amount of heat energy delivered to the tumors must be confirmed. If it cannot be confirmed before hyperthermia, normal tissues may also be heated, leading to possible necrosis. In a previous study, the thermal distribution was calculated using mass density distribution with CT image. The previous study was not performed various evaluations of accuracy for the developed thermal distribution prediction algorithm. In this study, the developed thermal distribution prediction algorithm was evaluated by comparing the phantom with the measured temperature and a commercial simulation software (Sim4Life) has been used as a reference data for hyperthermia studies. The difference between the measured temperature and the commercial simulation software (Sim4Life) was within 3%, and the difference between the measured temperature and the developed thermal distribution algorithm was also within 2%. The difference between the developed thermal distribution algorithm and the commercial simulation software was also within 3%. The thermal distribution algorithm developed in this study could predict the internal temperature of the patient before hyperthermia and increase the treatment accuracy by preventing necrosis from occurring in normal organs. In addition, it could easily predict the temperatures for hyperthermia without modeling CT images taken for the diagnosis of lesions.
机译:在热疗之前,必须确认输送到肿瘤的热能量。如果在热疗前不能确认,也可以加热正常组织,导致可能的坏死。在先前的研究中,使用CT图像的质量密度分布计算热分布。之前的研究未对显影的热分布预测算法进行各种评估。在该研究中,通过将幻像与测量的温度进行比较和商业仿真软件(SIM4Life)作为热疗研究的参考数据来评估所发育的热分布预测算法。测量温度和商业仿真软件(SIM4Life)之间的差异在3%范围内,测量温度与发育的热分布算法之间的差异也在2%以内。发达的热分配算法与商业仿真软件之间的差异也在3%范围内。本研究开发的热分布算法可以预测热疗前患者的内部温度,并通过预防正常器官发生的坏死来增加治疗准确性。此外,它可以容易地预测热疗的温度,而无需建模CT图像才能诊断病变。

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