“…e segmentation techniques play an essential role in the diagnosis, feature extraction, and classification accuracy of breast masses as benign and malignant. Different deep learning segmentation methods are used for breast cancer images such as FCN [8], U-Net [9,26,27], Segmentation Network (SegNet) [28], Full Resolution Convolutional Network (FrCN) [29], mask Region-Based Convolutional Neural Networks mask (RCNNs) [11,30], Attention guided dense up-sampling network(Aunet) [31], Residual attention U-Net model (RUNet) [32], conditional Generative Adversarial Networks (cGANs) [33], Densely connected U-Net and attention gates (AGs) [34], and Conditional random field model (CRF) [35].…”