CSR U-Net: A Novel Approach for Enhanced Skin Cancer Lesion Image Segmentation

Early detection is very critical step in skin cancer diagnosis and treatment. This paper introduces a novel deep learning approach for skin cancer lesion image segmentation model, CSR U-Net: Channel–Spatial Regularized U-Net. The proposed model focuses on both channel attention and spatial attention with additional optimized regularization methods to prevent model overfitting. The paper discusses the implementation of U-Net, Attention U-Net, Residual U-Net models, and CSR U-Net and also compares the results. The segmentation task often has challenges due to variations in skin tones, quality of the image, variations in the lesion, noise, class imbalance, and boundary delineation. This research aims to create a better high performing model CSR U-Net that over comes the above-said challenges.