Automatic Breast Tumor Diagnosis in MRI Based on a Hybrid CNN and Feature-Based Method Using Improved Deer Hunting Optimization Algorithm

Table 1

Recent studies in breast tumor identification.

Authors	Year	Approach	Dataset	Average accuracy (%)
Ibraheem et al. [4]	2019	Feature extracted with DWT and then reduced to 13 features	Reference image database to evaluate response (RIDER)	98.03
		Classification: CAD-SVM
Navid et al. [5]	2020	Segmentation WCO based on image thresholding method	MIAS	87.5
Toğaçar et al. [6]	2020	Classification: hypercolumn technique	BreakHis	98.80
Ibrahim et al. [3]	2020	Segmentation based on a chaotic Salp swarm algorithm (CSSA)	Mastology research with Infrared image (DMR-IR)	92
Hu et al. [2]	2020	Feature: DCE and T2w sequences	mpMRI	95
		Classification: CNN- SVM
Alanazi et al. [7]	2021	Classification: CNN- SVM	Kaggle 162 H&E	87
Ma et al. [8]	2021	Classification: 1D-CNN model	Spectral data	98