提高多模态诊断系统拉曼光谱效率的方法

Alexey S. Kovtunenko, A. Bilyalov, Liaisan Bakirova, N. Topolskii, G. Voronkov, E. Grakhova, R. Kutluyarov
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引用次数: 0

摘要

术中诊断是现代外科手术的重要工具,它提高了肿瘤切除的准确性,减少了对健康组织损伤的可能性。本文考虑通过多模态方法提高术中诊断的准确性:拉曼光谱和光学相干断层扫描的结合。研究表明,当与机器学习方法结合使用时,诊断系统的准确率可高达98%。为了进一步提高精度,建议考虑将其他类型的拉曼光谱作为多模态系统的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methods to increase the Raman spectroscopy efficiency in multimodal diagnostic systems
An intraoperative diagnostic is a vital tool in modern surgery, and it improves the accuracy of tumor removal and reduces the likelihood of damage to healthy tissue. The paper considers increasing the accuracy of intraoperative diagnostics through multimodal methods: a combination of Raman spectroscopy and optical coherence tomography. It is shown that when used in conjunction with machine learning methods, the accuracy of the diagnostic system can be up to 98%. To further increase the accuracy, it is advisable to consider other types of Raman spectroscopy as part of a multimodal system.
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