Prediction of injury depth in photothermal treatment based on the machine learning

Jialing Zhang; Yali Huang; Zhaowei Zhong; Dezi Li; Zhiwei Hu; Shulian Wu; Zhifang Li; Youwu He

doi:10.1117/12.2573811

10 October 2020 Prediction of injury depth in photothermal treatment based on the machine learning

Jialing Zhang, Yali Huang, Zhaowei Zhong, Dezi Li, Zhiwei Hu, Shulian Wu, Zhifang Li, Youwu He

Proceedings Volume 11549, Advanced Optical Imaging Technologies III; 115491A (2020) https://doi.org/10.1117/12.2573811
Event: SPIE/COS Photonics Asia, 2020, Online Only

Conference Poster

Abstract

To explore the damage range in the photothermal treatment at different temperatures, a temperature-feedback photothermal control system was developed. The system used an infrared thermal imager to noninvasively monitor the temperature .so it could avoid the damage caused by thermocouple measurement and apply the PID controller to achieve the desired temperature(1). the range of damage at the surface and the depth of internal damage were recorded at the different temperatures, which are based on the temperature-feedback photothermal control system. Finally, the recorded data are used to fit the curve by linear regression, and the damage depth was predicted according to the range of external damage at the surface. The technique could be a potential application for monitoring tumor treatment.

Conference Presentation

Citation Download Citation

Jialing Zhang, Yali Huang, Zhaowei Zhong, Dezi Li, Zhiwei Hu, Shulian Wu, Zhifang Li, and Youwu He "Prediction of injury depth in photothermal treatment based on the machine learning", Proc. SPIE 11549, Advanced Optical Imaging Technologies III, 115491A (10 October 2020); https://doi.org/10.1117/12.2573811

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