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通过深度学习增强微波成像进行热疗监测:数值评估

Hyperthermia Treatment Monitoring via Deep Learning Enhanced Microwave Imaging: A Numerical Assessment.

作者信息

Yago Ruiz Álvaro, Cavagnaro Marta, Crocco Lorenzo

机构信息

CNR-IREA National Research Council of Italy, Institute for Electromagnetic Sensing of the Environment, 80124 Naples, Italy.

Department of Information Engineering, Electronics, and Telecommunications, University of Rome "La Sapienza", 00184 Rome, Italy.

出版信息

Cancers (Basel). 2023 Mar 11;15(6):1717. doi: 10.3390/cancers15061717.

Abstract

The paper deals with the problem of monitoring temperature during hyperthermia treatments in the whole domain of interest. In particular, a physics-assisted deep learning computational framework is proposed to provide an objective assessment of the temperature in the target tissue to be treated and in the healthy one to be preserved, based on the measurements performed by a microwave imaging device. The proposed concept is assessed in-silico for the case of neck tumors achieving an accuracy above 90%. The paper results show the potential of the proposed approach and support further studies aimed at its experimental validation.

摘要

本文探讨了在整个感兴趣区域内进行热疗治疗时的温度监测问题。具体而言,提出了一种物理辅助的深度学习计算框架,以基于微波成像设备所进行的测量,对待治疗的目标组织和要保留的健康组织中的温度提供客观评估。针对颈部肿瘤的情况,在计算机模拟中对所提出的概念进行了评估,其准确率达到了90%以上。论文结果显示了所提方法的潜力,并支持旨在对其进行实验验证的进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f5a/10046415/e57daafec967/cancers-15-01717-g001.jpg

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