A Novel Intelligent System for Brain Tumor Diagnosis Based on a Composite Neutrosophic-Slantlet Transform Domain for Statistical Texture Feature Extraction

Table 6

Comparison of proposed classification accuracy with recent techniques.

Author	Year	Techniques used on the same BraTS17 dataset		Classification accuracy (%)
		Feature extraction	Classifier
Banerjee et al. [10]	2017	ConvNet model	DCNN	97.19
Cho et al. [51]	2018	Radiomic approach (ISZM, GLCM, SFB, and HBF)	Logistic, SVM, and RF	92.92
Sharif et al. [9]	2019	Scattering transform, wavelet transform, and local Gabor binary pattern	HCS-DBN	94.50
Raju et al. [55]	2019	SFTA and LBP	MSVM	96.90
Proposed work		GLRLM—composite NS-SLT	SVM-NN, DT-NN, KNN-NN, and NB-NN	98.94