Table 2.

Mammogram studies summarized

Pre-processing technique	Size of images	Compared with	Model used	Novel technique	Performance	Dataset used	Ref., year
Conversion to same image format, Otsu thresholding [59], noise removal, image sharpening, CLAHE for image enhancement, ROI cropping, image resizing, rotation, flip	208$\times$208	Previous studies	Customized CNN	Customized CNN to classify both ROI patches and whole images	Acc 96.52 $\%$, SN 96.55 $\%$, SP 96.49 $\%$, AUC 0.98	MIAS, DDSM, INbreast	[58], 2021
Image enhancement using CLAHE, rotation	227$\times$227		AlexNet + SVM	Pre-trained AlexNet customized to classify 2 classes	Acc 87.2 $\%$, AUC 0.94	DDSM, CBIS DDSM	[55], 2019
Feature-wise data augmentation, patches, rotation, flip	128$\times$128	Previous studies	Customized CNN	CNNI-BCC: feature wise pre-processing + CNN classification + interactive lesion detector	SN 89.47, SP 90.71, acc 90.5, AUC 0.90	MIAS	[54], 2019
Noise reduction, contrast enhancement	48$\times$48		CNN + ELM	Fused feature set using CNN + fused feature set used by ELM for classification	SN 85.1, SP 88.02, acc (benign) 88.5, acc (malignant) 84.5, AUC 0.923		[56], 2019
Breast region extraction, pectoral muscle suppression, breast mask creation, contrast enhancement, block creation,		Previous studies	Customized CNN	Block-based CNN and decision mechanism	AUC 0.95, acc 94.68 $\%$, SN 93.33 $\%$, SP 95.31 $\%$	MIAS	[52], 2019
ROI patches, rotation, random X and Y flip		AlexNet, GoogleNet, ResNet, VGGNet	ResNet + VGGNet	ResNet for Class Activation Maps, VGGNet for classification	Overall acc 92.53 $\%$	CBIS-DDSM	[62], 2018
Rotation, reflection, CLAHE, 2-D DWT, Discrete Curvelet Transform, Dense Scale Invariant Feature Transform for clear edges	128$\times$128	Previous studies	CNN-DW (discrete wavelet), CNN-DT (curvelet transform)	CNN-DW/CNN-DT + SVM classifier	CNN-DW: acc 81.83 $\%$, SN 87.6 $\%$, SP 81.9 $\%$; CNN-CT: acc 83.74 $\%$, SN 88.8 $\%$, SP 80.1 $\%$	IRMA	[63], 2017
Patch extraction (sliding window),	224$\times$224	VGG16, ResNet50, InceptionV3	InceptionV3	Customized Inception V3 for classification and detection	Acc 88.86 $\%$	CBIS-DDSM, INbreast	[57], 2019
Image format conversion, ROI extraction	224$\times$224	AlexNet, VGG-16, VGG-19, ResNet 50, ResNet 101,ResNet152, GoogLeNet, Inception-BN (v2)	ResNet101	Modified pre-trained model	Acc 85.9 $\%$	DDSM-400, CBIS-DDSM	[67], 2019