2013
DOI: 10.1088/1054-660x/23/6/065601
|View full text |Cite
|
Sign up to set email alerts
|

Near-infrared confocal micro-Raman spectroscopy combined with PCA–LDA multivariate analysis for detection of esophageal cancer

Abstract: The diagnostic capability of using tissue intrinsic micro-Raman signals to obtain biochemical information from human esophageal tissue is presented in this paper. Near-infrared micro-Raman spectroscopy combined with multivariate analysis was applied for discrimination of esophageal cancer tissue from normal tissue samples. Micro-Raman spectroscopy measurements were performed on 54 esophageal cancer tissues and 55 normal tissues in the 400-1750 cm −1 range. The mean Raman spectra showed significant differences … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
22
0

Year Published

2015
2015
2022
2022

Publication Types

Select...
8
2

Relationship

0
10

Authors

Journals

citations
Cited by 32 publications
(22 citation statements)
references
References 22 publications
0
22
0
Order By: Relevance
“…It is evident that certain biochemical changes associated with skin malignancies can be successfully identified by Raman spectroscopy. To reduce the high number of parameters needed to characterize the variance in the acquired spectral datasets, researchers typically utilize multivariate statistical methods to generate linear discriminant models of classification [ 67 ]. In the subsequent section we also refer to the sensitivity and specificity of these models for BCC, SCC and MM.…”
Section: Resultsmentioning
confidence: 99%
“…It is evident that certain biochemical changes associated with skin malignancies can be successfully identified by Raman spectroscopy. To reduce the high number of parameters needed to characterize the variance in the acquired spectral datasets, researchers typically utilize multivariate statistical methods to generate linear discriminant models of classification [ 67 ]. In the subsequent section we also refer to the sensitivity and specificity of these models for BCC, SCC and MM.…”
Section: Resultsmentioning
confidence: 99%
“…Among other reported studies, Chen et al . noted changes in protein structure, a decrease in the relative amount of lactose and an increase in the proportion of tryptophan, collagen, and phenylalanine content in esophageal cancer tissues when compared with esophageal tissues from healthy subjects . By using principal component analysis and linear discriminant analysis, they achieved 87% sensitivity and 71% specificity in discriminating cancerous tissue from normal esophageal tissues.…”
Section: Current Applications Of Raman Spectroscopy In Esophageal Dismentioning
confidence: 99%
“…DA computes a set of discriminant functions based on linear combinations of variables that maximize the variance between groups and minimize the variance within groups according to Fisher's criterion. Sometimes it is very useful to combine both PCA and LDA approaches (called PC-LDA model), which improves the efficiency of classification as it automatically finds the most diagnostically significant features [29][30][31]. SVMs are kernel-based algorithms that transform data into a high-dimensional space and construct a hyperplane that maximizes the distance to the nearest data point of any of the input classes.…”
Section: Classification and Clustering Modelsmentioning
confidence: 99%