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使用分散反射光谱和人工智能精确估计皮肤组织中的甲基红蛋白和氧和度

Isra Sahli¹, Wesam Bachir², Moustafa Sayem El-Daher¹

¹Biomedical Photonics Laboratory, Higher Institute for Laser Research and Applications, Damascus University, Damascus, Syria.

Journal of biophotonics

|February 27, 2025

概括

这项研究引入了一种新的人工神经网络方法,用于准确地测量非侵入性地测量甲血球度. 该技术使用扩散反射光谱 (DRS) 精确检测血液氧和甲血球蛋白水平.

科学领域:

生物医学光学生物医学光学
医学诊断医学诊断医学诊断
医疗保健中的机器学习

背景情况:

甲血球蛋白血症需要精确的监测.
需要使用非侵入性的方法来评估血液氧化和甲血球蛋白.
分散反射光谱 (DRS) 显示了组织分析的潜力.

研究的目的:

开发和验证一种用于准确估计甲血球度的非侵入性方法.
利用人工神经网络 (ANN) 来分析分散反射频谱.
使用光谱数据,区分甲血球蛋白与血红蛋白.

主要方法:

模拟了66种皮肤组织光谱,使用四层模型与不同氧和甲血球蛋白水平进行模拟.
在可见和近红外范围内采用基于多纤维探针的DRS设置.
开发了一种用于光谱分析的新型人工神经网络模型.

主要成果:

达到0.0392%的甲血球度的平均绝对误差 (MAE).
在模拟数据上实现了0.0273%的氧和MAE.
通过使用人类受试者的DRS光谱来实验验证该方法.

结论:

宽带DRS与ANN相结合,可以准确,非侵入性地估计甲红蛋白.
该方法可以区分甲红蛋白和血红蛋白水平的微妙变化.
这种技术为临床诊断提供了一个有前途的方法.

关键词:

蒙特卡洛模拟的蒙特卡洛模拟.人工神经网络的人工神经网络扩散反射光谱学扩散反射光谱学甲基血球蛋白是一种甲基血球蛋白.

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