基于近红外光谱的预处理及组合方法  

Pretreatment and Combined Method Based on Near Infrared Spectroscopy

作　　者：张朱珊莹 顾瀚文 谢凯文 江河 谢勤岚[1,2,3] 撒继铭 Zhang Zhushanying;Gu Hanwen;Xie Kaiwen;Jiang He;Xie Qinlan;Sa Jiming(College of Biomedical Engineering,South-Central University for Nationalities,Wuhan,Hubei 430074,China;Key Laboratory of Cognitive Science,State Ethnic Affairs Commission,South-Central University for Nationalities,Wuhan,Hubei 430074,China;Hubei Key Laboratory of Medical Information Analysis and Tumor Diagnosis&Treatment,Wuhan,Hubei 430074,China;School of Information Engineering,Wuhan University of Technology,Wuhan,Hubei 430070,China)

机构地区：[1]中南民族大学生物医学工程学院,湖北武汉430074 [2]中南民族大学认知科学国家民委重点实验室,湖北武汉430074 [3]医学信息分析及肿瘤诊疗湖北省重点实验室,湖北武汉430074 [4]武汉理工大学信息工程学院,湖北武汉430070

出　　处：《激光与光电子学进展》2021年第16期464-471,共8页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(61501526,61178087);中南民族大学中央高校基本科研业务费专项资金(CZQ18014)。

摘　　要：针对复杂样品光谱信号存在的杂散光、噪声、基线漂移等因素对定量分析结果的影响,提出了一种基于近红外光谱的预处理及组合方法。首先,对选取的2组数据分别进行无预处理和单一预处理。然后,将9种预处理方法按照效果分为四类,包括尺度缩放、基线校正、散射校正和平滑处理。最后,选出每类预处理方法中的最优预处理方法进行组合研究,并根据建模后的交互验证均方根误差选出最优的预处理方法。实验结果表明,针对不同数据集采用合适的预处理组合方法能提高建模效果,但不同数据集信息与复杂性间的差异会导致不同的最优预处理方法,且最优预处理方法与预测组分和原始光谱有关。因此,将预处理方法按照效果进行分类并组合可得到最佳预处理效果。Aiming at the influence of stray light,noise,baseline drift and other factors in the spectral signal of complex samples on the quantitative analysis results,this paper proposes a pretreatment and combined method based on near-infrared spectroscopy.First,no pretreatment and single pretreatment on 2 selected datasets is performed.Then,9 pretreatment methods are divided into four categories according to their effects,including scale scaling,baseline correction,scattering correction and smoothing.Finally,the optimal pretreatment method of each type of pretreatment method is selected for combined research,and the optimal pretreatment method is selected according to the root mean square error cross-validation after modeling.Experimental results show that the use of appropriate pretreatment combination methods for different data sets can improve the modeling effect,while the difference between the information and complexity of different data sets will lead to different optimal pretreatment methods,and the optimal pretreatment method is related to the predicted components and the original spectra.Therefore,the best pretreatment effect can be obtained by classifying and combining the pretreatment methods according to their effects.

关 键 词：医用光学 预处理方法 复杂样品 方法选择 参数优化 偏最小二乘法 

分 类 号：O433.4[机械工程—光学工程]