Table 5.

Performance of the proposed model and machine learning classifiers on Figshare.

Metrics	Tumor type	TP	TN	FP	FN	Sensitivity	Specificity	PPV	NPV	Accuracy	DSC
Method
Deep CNN + random forest	Glioma	343	399	11	13	0.963	0.973	0.968	0.968	96.8%	96.6%
	Meningioma	169	580	09	08	0.954	0.984	0.949	0.986	97.8%	95.2%
	Pituitary	221	524	10	11	0.952	0.981	0.956	0.979	97.3%	95.4%
Deep CNN + SVM-RBF	Glioma	348	401	09	08	0.977	0.978	0.974	0.980	97.7%	97.6%
	Meningioma	171	581	08	06	0.966	0.986	0.955	0.989	98.1%	96.0%
	Pituitary	225	528	06	07	0.970	0.988	0.974	0.986	98.3%	97.1%
Deep CNN + ELM	Glioma	341	397	13	15	0.957	0.968	0.963	0.963	96.3%	96.0%
	Meningioma	166	579	10	11	0.937	0.983	0.943	0.981	97.2%	94.0%
	Pituitary	220	521	13	12	0.948	0.975	0.944	0.977	96.7%	94.6%