. 2013 Jan 8;26(4):731–739. doi: 10.1007/s10278-012-9556-5

Table 2.

3-D US image classification results of breast tumors using neural network with all proposed features and V_I, respectively

Sonographic classification	NN with all features		NN with V_I
Sonographic classification	Benign^a	Malignant^a	Benign^a	Malignant^a
Benign	TN 47	FN 7	TN 42	FN 8
Malignant	FP 13	TP 46	FP 18	TP 45
Total	60	53	60	53

TP true positive, TN true negative, FP false positive, FN false negative

^aHistological finding. Accuracy = (TP + TN)/(TP + TN + FP + FN); sensitivity = TP/(TP + FN); specificity = TN/(TN + FP); positive predictive value = TP/(TP + FP); negative predictive value = TN/(TN + FN)