Radiomics Analysis Based on Automatic Image Segmentation of DCE-MRI for Predicting Triple-Negative and Nontriple-Negative Breast Cancer

Table 2

Accessible methods for all steps in the radiomics pipeline.

Radiomics pipeline	Method
Data normalization	Min-max	Zscore	Mean	None
Dimension reduction	PCA	PCC
Feature selection	ANOVA	KW	RFE	Relief
Classifier	SVM	LDA	MP	RF	LR	LASSO	AB	DT	GP	NB

(PCA: principal component analysis; PCC: Pearson correlation coefficient; ANOVA: analysis of variance; KW: Kruskal–Wallis test; RFE: recursive feature elimination; SVM: support vector machine; LDA: linear discriminant analysis; MP: multilayer perceptron, RF: recursive feature; LR: linear regression; LASSO: least absolute shrinkage and selection operator; AB: Adaboost; DT: decision tree; GP: Gaussian process; NB: naïve Bayes).