Selection of Spatiotemporal Features in Breast MRI to Differentiate between Malignant and Benign Small Lesions Using Computer-Aided Diagnosis

Table 2

Combined classification of the feature groups and different classification methods. Abbreviations: linear discriminant analysis (LDA), naive Bayes linear discriminant analysis (N.B.LDA), quadratic discriminant analysis (QDA), naive Bayes quadratic discriminant analysis (N.B.QDA), and Fisher’s linear discriminant (FLDA).

Features	Correctly classified (%)
	LDA	N.B.LDA	QDA	N.B.QDA	FLDA
Contour features	64.5	74.2	67.7	77.4	64.5
Scaling index features	67.7	71.0	61.3	51.6	67.7
Tumor RSIE features	64.5	74.2	74.2	77.4	64.5
Contour RSIE features	64.5	74.2	54.8	54.8	64.5
Geometric moments	51.6	54.8	51.6	64.5	51.6
Krawtchouk moments	71.0	74.2	77.4	71.0	74.2