Error removal by orthogonal subtraction (EROS): a customised pre‐treatment for spectroscopic data

Abstract

aIn some applications of diffuse reflectance spectroscopy there may be substantial variability between the spectra from replicate measurements of what is nominally the same sample. A method called error reduction by orthogonal subtraction (EROS) is proposed to ameliorate the effects of this. The first step is to use principal component analysis (PCA) to identify the structure in the variability of replicate measurements. This is followed by subtraction of the modelled effects from the original spectral data matrix X by projection onto the subspace orthogonal to factors derived from the PCA. An application to the clinical diagnosis of colon lesions is presented, in which pre-treatment of spectra using the proposed method is successful in reducing the complexity and increasing both the accuracy and interpretability of the subsequent classification model.

Calibration transfer of intact olive NIR spectra between a pre-dispersive instrument and a portable spectrometer

“…An efficient method 118 for finding this subspace is to identify the influenced subspace and to remove it by 119 means of an orthogonal projection. Depending on the way the detrimental subspace is 120 identified, several methods have been proposed, as independent interference reduction 121 (IIR) (Hansen, 2001), external parameter orthogonalization (EPO) (Roger et al, 2003), 122 transfer by orthogonal projection (TOP) (Andrew and Fearn, 2004), dynamic orthogonal 123 projection (DOP) (Zeaiter et al, 2006) and error removal by orthogonal subtraction 124 (EROS) (Zhu et al, 2008). 125…”

Probe pressure effects on human skin diffuse reflectance and fluorescence spectroscopy measurements

“…11,33,34 Zhu et al proposed a statistical technique called error removal by orthogonal subtraction (EROS) that reduced variability in spectra from replicates measurements of the same sample. 35 Some of the sources of spectra variability are small changes in angle and probe pressure. EROS was reported to reduce complexity and increase accuracy of qualitative classification on colon lesions 35 and Barrett's esophagus.…”

“…35 Some of the sources of spectra variability are small changes in angle and probe pressure. EROS was reported to reduce complexity and increase accuracy of qualitative classification on colon lesions 35 and Barrett's esophagus. 36 Our results showed that short-term light probe pressure has negligible effects under clinical measurements conditions, thus we do not think it necessary to add an additional step in our postprocessing procedure.…”

Chemometric Feature Selection and Classification of <i>Ganoderma lucidum</i> Spores and Fruiting Body Using ATR-FTIR Spectroscopy

“…Then LDA focuses on finding a linear combination of the new variables, provided either by PCA or PLS, to construct canonical variate which best separates the two groups. Using pretreated spectral data described in Section 2.3, classification rules were derived using principal component discriminant analysis (PCDA) [14]- [16] and partial least squares discriminant analysis (PLSDA) [15]- [17]. The PCDA involves an initial PCA on the pre-treated spectra followed by a LDA performed on the first k PCs' scores.…”