Abstract
Focused ultrasound-based methods are widely used in various areas of medicine for vascular damage coagulation in limbs and internal organs, venous obliteration, and ablation of breast and thyroid tumors. To plan heat exposure and control its effectiveness, it is necessary to monitor temperature during the treatment procedure. The article proposes two technologies for such monitoring, namely infrared thermography and ultrasound thermometry using neural network methods.
The proposed method of temperature recovery inside the material from surface temperature measurements enhances the potential of infrared thermography and improves the calibration accuracy of ultrasound thermometry.
The proposed method for determining the ultrasound signal shift has not been previously used for ultrasound thermometry. While maintaining acceptable accuracy, it can significantly reduce the computation time, which makes it possible to use it in real time.
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The study was carried out in the framework of Project No. RFMEFI57818X0263 supported by the Education and Science Ministry of the Russian Federation for 2018–2019.
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Yukhnev, A., Tarkhov, D., Gataulin, Y., Ivanova, Y., Berkovich, A. (2019). Neural Network Methods of HIFU-Therapy Control by Infrared Thermography and Ultrasound Thermometry. In: Lu, H., Tang, H., Wang, Z. (eds) Advances in Neural Networks – ISNN 2019. ISNN 2019. Lecture Notes in Computer Science(), vol 11555. Springer, Cham. https://doi.org/10.1007/978-3-030-22808-8_59
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